MAT 240 Project One
Project One Guidelines and Rubric.html
MAT 240 Project One Guidelines and Rubric
Competencies
In this project, you will demonstrate your mastery of the following competencies:
- Apply statistical techniques to address research problems
- Perform regression analysis to address an authentic problem
Overview
The purpose of this project is to have you complete all of the steps of a real-world linear regression research project starting with developing a research question, then completing a comprehensive statistical analysis, and ending with summarizing your research conclusions.
Scenario
You have been hired by the D. M. Pan National Real Estate Company to develop a model to predict housing prices for homes sold in 2019. The CEO of D. M. Pan wants to use this information to help their real estate agents better determine the use of square footage as a benchmark for listing prices on homes. Your task is to provide a report predicting the housing prices based square footage. To complete this task, use the provided real estate data set for all U.S. home sales as well as national descriptive statistics and graphs provided.
Directions
Using the Project One Template located in the What to Submit section, generate a report including your tables and graphs to determine if the square footage of a house is a good indicator for what the listing price should be. Reference the National Statistics and Graphs document for national comparisons and the Real Estate Data Spreadsheet spreadsheet (both found in the Supporting Materials section) for your statistical analysis.
Note: Present your data in a clearly labeled table and using clearly labeled graphs.
Specifically, include the following in your report:
Introduction
- Describe the report: Give a brief description of the purpose of your report.
- Define the question your report is trying to answer.
- Explain when using linear regression is most appropriate.
- When using linear regression, what would you expect the scatterplot to look like?
- Explain the difference between predictor (x) and response (y) variables in a linear regression to justify the selection of variables.
Data Collection
- Sampling the data: Select a random sample of 50 houses. Describe how you obtained your sample data (provide Excel formulas as appropriate).
- Identify your predictor and response variables.
- Scatterplot: Create a scatterplot of your predictor and response variables to ensure they are appropriate for developing a linear model.
Data Analysis
- Histogram: Create a histogram for each of the two variables.
- Summary statistics: For your two variables, create a table to show the mean, median, and standard deviation.
- Interpret the graphs and statistics:
- Based on your graphs and sample statistics, interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for house sales and square footage.
- Compare and contrast the center, shape, spread, and any unusual characteristic for your sample of house sales with the national population (under Supporting Materials, see the National Summary Statistics and Graphs House Listing Price by Region PDF). Determine whether your sample is representative of national housing market sales.
Develop Your Regression Model
- Scatterplot: Provide a scatterplot of the variables with a line of best fit and regression equation.
- Based on your scatterplot, explain if a regression model is appropriate.
- Discuss associations: Based on the scatterplot, discuss the association (direction, strength, form) in the context of your model.
- Identify any possible outliers or influential points and discuss their effect on the correlation.
- Discuss keeping or removing outlier data points and what impact your decision would have on your model.
- Calculate r: Calculate the correlation coefficient (r).
- Explain how the r value you calculated supports what you noticed in your scatterplot.
Determine the Line of Best Fit. Clearly define your variables. Find and interpret the regression equation. Assess the strength of the model.
- Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables.
- Interpret regression equation: Interpret the slope and intercept in context. For example, answer the questions: what does the slope represent in this situation? What does the intercept represent? Revisit the Scenario above.
- Strength of the equation: Provide and interpret R-squared.
- Determine the strength of the linear regression equation you developed.
- Use regression equation to make predictions: Use your regression equation to predict how much you should list your home for based on the assumed square footage of your home at 1500 square feet.
Conclusions
- Summarize findings: In one paragraph, summarize your findings in clear and concise plain language for the CEO to understand. Summarize your results.
- Did you see the results you expected, or was anything different from your expectations or experiences?
- What changes could support different results, or help to solve a different problem?
- Provide at least one question that would be interesting for follow-up research.
You can use the following tutorial that is specifically about this assignment. Make sure to check the assignment prompt for specific numbers used for national statistics. The videos may use different national statistics. You should use the national statistics posted with this assignment.
What to Submit
To complete this project, you must submit the following:
Project One Template Word Document : Use this template to structure your report and submit the finished version as a Word document. Also submit your Excel file showing all steps and calculations used in the report.
Supporting Materials
The following resources may help support your work on the project:
Document: National Summary Statistics and Graphs Real Estate Data PDF Use this data for input in your project report.
Spreadsheet: Real Estate Data Spreadsheet Use this data for input in your project report.
Tutorial: Downloading Office 365 Programs PDF Use this tutorial for support with Office 365 programs.
Use these tutorials for support with the Excel functions you will use in the project:
- Tutorial: Random Sampling in Excel PDF
- Tutorial: Scatterplots in Excel PDF
- Tutorial: Descriptive Statistics in Excel PDF
- Tutorial: Creating Histograms in Excel PDF
AI Usage
If you use gen AI tools to support your work on this assignment, be sure to follow these AI usage guidelines. You must acknowledge your use of these tools in your work. Guidelines on how to cite AI tools can be found in this Shapiro Library guide.
Project One Rubric
| Criteria | Exceeds Expectations | Meets Expectations | Partially Meets Expectations | Does Not Meet Expectations | Value |
|---|---|---|---|---|---|
| Introduction: Describe the Report | Exceeds expectations in an exceptionally clear manner (100%) | Defines the question the report is trying to answer, and explains when using linear regression is most appropriate, what the scatterplot will look like, and the difference between response and predictor variables in a linear regression to justify the selection of variables (85%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include inaccurately defining the question, the appropriateness and justification of the linear regression model or the selection of variables, or introduction lacking essential detail and clarity (55%) | Does not attempt criterion (0%) | 10 |
| Data Collection: Sampling the Data | N/A | Selects a random sample of 50 houses and describes how the data was obtained. Identifies the response and predictor variables (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include inaccurate selection of random sample or inaccurate or unclear selection of response and predictor values (55%) | Does not attempt criterion (0%) | 5 |
| Data Collection: Scatterplot | N/A | Creates a scatterplot of the predictor and response variables to ensure they are appropriate for developing a linear model (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include inaccurate scatterplot representation of the information or inaccurate or unclear determination of response and predictor variables (55%) | Does not attempt criterion (0%) | 5 |
| Data Analysis: Histogram | N/A | Creates histograms for the two variables (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include histograms that are created incorrectly or are inaccurate (55%) | Does not attempt criterion (0%) | 5 |
| Data Analysis: Summary Statistics | N/A | Creates a table to show the mean, median, and standard deviation for two variables (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include table showing mean, median and standard deviation that are inaccurate or created incorrectly (55%) | Does not attempt criterion (0%) | 5 |
| Data Analysis: Interpret Graphs and Statistics | N/A | Interprets the graphs and statistics center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for the two variables based on the graphs and sample statistics, and compares and contrasts with national housing market sales and determines if their sample is representative (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include inaccurate or cursory interpretation of the characteristics of the graph and statistics or inaccurate or cursory comparison or contrast with the national market (55%) | Does not attempt criterion (0%) | 5 |
| Develop Regression Model: Scatterplot | N/A | Provides a scatterplot with a line of best fit; explains if a regression model is appropriate based on the scatterplot (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include Inaccurate scatterplot or line of best fit or explanation of regression model appropriateness that is inaccurate or cursory (55%) | Does not attempt criterion (0%) | 5 |
| Develop Regression Model: Discuss Associations | Exceeds expectations in an exceptionally clear manner (100%) | Discusses the association in the context of the model based on scatterplot (direction, strength, form), includes possible outliers or influential points, discusses effect on correlation, and discusses impact of keeping or removing outliers (85%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include discussion of association in the context of the scatterplot, possible outliers, influential points and impact on correlation, or impacts of keeping or removing outliers that is inaccurate or cursory (55%) | Does not attempt criterion (0%) | 10 |
| Develop Regression Model: Calculate r | Exceeds expectations in an exceptionally clear manner (100%) | Calculates the correlation coefficient (r) and explains how the calculated r value supports what was noticed in the scatterplot (85%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include inaccurate calculation for r or explanation of how the r value supports the scatterplot that is inaccurate or cursory (55%) | Does not attempt criterion (0%) | 10 |
| Determine Line of Best Fit: Regression Equation | N/A | Writes the regression equation and clearly defines variables (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include regression equation that is written inaccurately or variables that are not clearly defined (55%) | Does not attempt criterion (0%) | 5 |
| Determine Line of Best Fit: Interpret Regression Equation | Exceeds expectations in an exceptionally clear manner (100%) | Interprets the slope and intercept in context (85%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include inaccurate interpretation of the slope and intercept (55%) | Does not attempt criterion (0%) | 10 |
| Determine Line of Best Fit: Strength of the Equation | N/A | Provides and interprets R-squared, determining the strength of the linear regression equation (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include inaccuracies in interpretation of R-squared or the determined strength of the regression equation (55%) | Does not attempt criterion (0%) | 5 |
| Determine Line of Best Fit: Use Regression Equation to Make Predictions | N/A | Uses a regression equation to predict how much you should list your home for based on the square footage of your home (100%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include misuse of regression equation or inaccurate prediction based on provided information (55%) | Does not attempt criterion (0%) | 5 |
| Conclusion: Summarize Findings | Exceeds expectations in an exceptionally clear manner (100%) | Summarizes findings and results in clear and concise plain language, includes whether the results were expected, changes that could support different results or that would help to solve a different problem; Includes a question for follow-up research (85%) | Shows progress toward meeting expectations, but with errors or omissions; areas for improvement may include inaccurately summarizing findings or results or summary that is cursory or missing required elements (55%) | Does not attempt criterion (0%) | 10 |
| Clear Communication | Exceeds expectations with an intentional use of language that promotes a thorough understanding (100%) | Consistently and effectively communicates in an organized way to a specific audience (85%) | Shows progress toward meeting expectations, but communication is inconsistent or ineffective in a way that negatively impacts understanding (55%) | Shows no evidence of consistent, effective, or organized communication (0%) | 5 |
| Total: | 100% |
course_documents/MAT 240 Project One Template.docx
Median Housing Price Model for D. M. Pan National Real Estate Company 2
[ Note: To complete this template, replace the bracketed text with your own content. Remove this note before you submit your outline.]
Report: Housing Price Prediction Model for D. M. Pan National Real Estate Company
[Your Name]
Median Housing Price Prediction Model for D. M. Pan National Real Estate Company 1
Southern New Hampshire University
Introduction
[ Describe the report: Define the question your report is trying to answer.]
[ Describe the report: Explain when using linear regression is the most appropriate.]
[ Describe the report: Explain when using linear regression what you would expect the scatterplot to look like.]
[ Describe the report: Explain the difference between predictor (x) and response (y) variables in a linear regression to justify the selection of variables.]
Data Collection
[ Sampling the data: Select a random sample of 50 houses. Describe how you obtained your sample data (provide Excel formulas as appropriate).]
[ Sampling the data: Identify your predictor and response variables.]
[ Scatterplot: Create and insert a correctly labeled scatterplot of your predictor and response variables to ensure they are appropriate for developing a linear model.]
Data Analysis
[ Histogram: Create and insert a histogram for the first variable. Be sure to include appropriate labels.]
[ Histogram: Create and insert a histogram for the second variable. Be sure to include appropriate labels.]
[ Summary statistics: Create and insert a table to show the summary statistics (mean, median, standard deviation) for both variables.]
[ Interpret the graphs and statistics: Interpret the center, spread, shape, and any unusual characteristic (outliers, gaps, etc.) for house sales and square footage.]
[ Interpret the graphs and statistics: Compare and contrast center, spread, shape, and any unusual characteristic for your sample of house sales with the national population. Also, determine whether your sample is representative of the national housing market sales. Note: In the learning management system, under Supporting Materials, see National Summary Statistics and Graphs Real Estate Data PDF.]
Develop Regression Model
[ Scatterplot: Create and insert the scatterplot of the variables with a line of best fit and the regression equation. [Based on your scatterplot, explain whether a regression model is appropriate.]
[ Discuss associations: Discuss the associations in the scatterplot, including the direction, strength, and form, in the context of your model.]
[ Discuss associations: Identify any possible outliers or influential points and discuss their effect on correlation.]
[ Discuss associations: Discuss keeping or removing outlier data points and what impact your decision would have on your model.]
[ Calculate r: Calculate the correlation coefficient and explain how the calculated r value supports what was noticed in your scatterplot.]
Determine the Line of Best Fit
[ Regression equation: Write the regression equation (i.e., line of best fit) and clearly define your variables.]
[ Interpret regression equation: Interpret the slope and intercept in context. For example, answer the questions: What does the slope represent in this situation? What does the intercept represent? Revisit the Scenario section in the learning management system.]
[ Strength of the equation: Provide and interpret R-squared. Determine the strength of the linear regression equation you developed.]
[ Use regression equation to make predictions: Use the regression equation to predict how much you should list your home for based on the assumed square footage of your home at 1500 square feet.]
Conclusions
[ Summarize findings: Summarize your findings in clear and concise plain language for the CEO to understand.]
[Summarize findings: Did you see the results you expected, or was anything different from your expectations or experiences?]
[Summarize findings: What changes could support different results, or help to solve a different problem?]
[Summarize findings: Provide at least one question that would be interesting for follow-up research.]
course_documents/National Summary Statistics and Graphs Real Estate Data.pdf
Summary Statistics for MAT 240 Real Estate Data (for dataset in Modules 2, 3, and 4)
n Mean Median Std. Dev. Min Q1 Q3 Max Listing price ($)
1,000 342,365 318,000 125,914 135,300 265,250 381,600 987,600
Cost per square foot ($)
1,000 169 166 41 71 139 191 344
Square feet
1,000 2,111 1,881 921 1,101 1,626 2,215 6,516
This graph shows the frequency for listing price.
This graph shows the frequency for square feet.
- National Summary Statistics and Graphs Real Estate Data
course_documents/MAT 240 Real Estate Data.xlsx
project 1 data
| Real Estate County Data for 2019 | |||||
| 2019 Data (n=1000) | |||||
| Region | State | County | listing price | $'s per square foot | square feet |
| East North Central | in | grant | 219,500 | $116 | 1,898 |
| East North Central | il | vermilion | 254,500 | $156 | 1,632 |
| East North Central | in | henry | 235,000 | $148 | 1,588 |
| East North Central | in | wayne | 203,800 | $141 | 1,441 |
| East North Central | il | coles | 220,800 | $117 | 1,893 |
| East North Central | il | macoupin | 197,600 | $111 | 1,783 |
| East North Central | in | vigo | 165,800 | $122 | 1,362 |
| East North Central | oh | jefferson | 246,500 | $136 | 1,814 |
| East North Central | il | jackson | 154,300 | $105 | 1,463 |
| East North Central | oh | marion | 149,700 | $116 | 1,296 |
| East North Central | mi | bay | 145,100 | $117 | 1,239 |
| East North Central | il | whiteside | 283,700 | $136 | 2,087 |
| East North Central | oh | trumbull | 243,000 | $133 | 1,827 |
| East North Central | in | madison | 229,100 | $187 | 1,224 |
| East North Central | il | knox | 205,100 | $118 | 1,740 |
| East North Central | il | stephenson | 235,600 | $140 | 1,682 |
| East North Central | il | macon | 212,900 | $128 | 1,659 |
| East North Central | in | delaware | 221,600 | $134 | 1,651 |
| East North Central | il | henry | 257,700 | $123 | 2,087 |
| East North Central | oh | seneca | 211,900 | $168 | 1,263 |
| East North Central | oh | darke | 160,800 | $114 | 1,416 |
| East North Central | oh | scioto | 204,200 | $131 | 1,562 |
| East North Central | oh | belmont | 172,500 | $101 | 1,710 |
| East North Central | oh | sandusky | 253,900 | $146 | 1,738 |
| East North Central | il | rock island | 166,300 | $127 | 1,305 |
| East North Central | oh | clark | 240,500 | $137 | 1,752 |
| East North Central | oh | columbiana | 241,400 | $164 | 1,469 |
| East North Central | in | howard | 304,300 | $152 | 1,996 |
| East North Central | oh | richland | 248,900 | $132 | 1,880 |
| East North Central | il | peoria | 187,900 | $131 | 1,434 |
| East North Central | il | la salle | 311,100 | $154 | 2,015 |
| East North Central | il | madison | 254,500 | $156 | 1,628 |
| East North Central | mi | wayne | 213,800 | $172 | 1,243 |
| East North Central | in | vanderburgh | 214,100 | $134 | 1,596 |
| East North Central | oh | mahoning | 207,500 | $123 | 1,688 |
| East North Central | il | williamson | 171,600 | $141 | 1,218 |
| East North Central | il | winnebago | 236,700 | $140 | 1,692 |
| East North Central | il | adams | 266,100 | $166 | 1,599 |
| East North Central | mi | saginaw | 171,800 | $118 | 1,452 |
| East North Central | oh | montgomery | 225,300 | $151 | 1,493 |
| East North Central | oh | allen | 227,600 | $147 | 1,550 |
| East North Central | oh | lucas | 228,300 | $115 | 1,978 |
| East North Central | oh | ashtabula | 177,000 | $107 | 1,658 |
| East North Central | oh | lawrence | 248,300 | $156 | 1,587 |
| East North Central | oh | huron | 199,700 | $147 | 1,359 |
| East North Central | il | tazewell | 278,700 | $165 | 1,693 |
| East North Central | oh | summit | 185,800 | $101 | 1,847 |
| East North Central | il | sangamon | 213,500 | $130 | 1,643 |
| East North Central | oh | ashland | 188,000 | $151 | 1,246 |
| East North Central | oh | tuscarawas | 270,700 | $149 | 1,815 |
| East North Central | oh | ross | 257,200 | $127 | 2,018 |
| East North Central | mi | shiawassee | 192,400 | $129 | 1,494 |
| East North Central | mi | calhoun | 266,200 | $130 | 2,042 |
| East North Central | il | kankakee | 148,700 | $115 | 1,293 |
| East North Central | in | lawrence | 270,600 | $137 | 1,978 |
| East North Central | wi | manitowoc | 181,400 | $140 | 1,294 |
| East North Central | il | st. clair | 201,400 | $164 | 1,225 |
| East North Central | mi | ingham | 222,500 | $125 | 1,777 |
| East North Central | il | mclean | 203,800 | $134 | 1,526 |
| East North Central | mi | jackson | 139,200 | $116 | 1,201 |
| East North Central | mi | isabella | 163,000 | $125 | 1,307 |
| East North Central | wi | wood | 266,500 | $144 | 1,853 |
| East North Central | mi | montcalm | 218,300 | $105 | 2,081 |
| East North Central | wi | grant | 243,200 | $121 | 2,014 |
| East North Central | oh | cuyahoga | 265,100 | $136 | 1,947 |
| East North Central | oh | stark | 201,000 | $163 | 1,230 |
| East North Central | oh | athens | 246,400 | $158 | 1,560 |
| East North Central | wi | milwaukee | 184,900 | $111 | 1,666 |
| East North Central | mi | lenawee | 191,500 | $118 | 1,628 |
| East North Central | wi | fond du lac | 135,300 | $103 | 1,312 |
| East North Central | in | st. joseph | 193,000 | $111 | 1,736 |
| East North Central | mi | ionia | 193,600 | $137 | 1,416 |
| East North Central | mi | genesee | 194,800 | $166 | 1,173 |
| East North Central | oh | muskingum | 188,300 | $94 | 1,999 |
| East North Central | il | ogle | 236,600 | $208 | 1,138 |
| East North Central | oh | washington | 324,400 | $156 | 2,081 |
| East North Central | oh | wayne | 256,700 | $129 | 1,986 |
| East North Central | mi | muskegon | 230,400 | $131 | 1,757 |
| East North Central | oh | pickaway | 265,700 | $143 | 1,853 |
| East North Central | mi | st. joseph | 188,500 | $135 | 1,397 |
| East North Central | il | champaign | 246,700 | $121 | 2,031 |
| East North Central | oh | knox | 192,200 | $127 | 1,510 |
| East North Central | oh | lorain | 226,200 | $126 | 1,789 |
| East North Central | wi | calumet | 226,400 | $111 | 2,033 |
| East North Central | mi | midland | 174,500 | $151 | 1,157 |
| East North Central | mi | marquette | 172,500 | $120 | 1,433 |
| East North Central | in | elkhart | 202,300 | $182 | 1,113 |
| East North Central | mi | monroe | 228,600 | $136 | 1,679 |
| East North Central | oh | lake | 225,900 | $135 | 1,676 |
| East North Central | mi | eaton | 189,900 | $96 | 1,976 |
| East North Central | wi | douglas | 461,400 | $129 | 3,581 |
| East North Central | wi | marathon | 431,200 | $119 | 3,638 |
| East North Central | il | dekalb | 347,500 | $97 | 3,574 |
| East North Central | in | marion | 323,300 | $95 | 3,408 |
| East North Central | in | allen | 398,000 | $113 | 3,525 |
| East North Central | oh | hancock | 380,300 | $94 | 4,028 |
| East North Central | in | lake | 470,600 | $109 | 4,316 |
| East North Central | wi | portage | 531,000 | $109 | 4,888 |
| East North Central | wi | rock | 513,100 | $104 | 4,950 |
| East North Central | oh | greene | 581,800 | $113 | 5,146 |
| West South Central | ar | baxter | 286,900 | $132 | 2,176 |
| West South Central | ar | benton | 232,900 | $138 | 1,690 |
| West South Central | ar | craighead | 251,100 | $110 | 2,285 |
| West South Central | ar | crawford | 172,900 | $100 | 1,734 |
| West South Central | ar | crittenden | 298,800 | $155 | 1,928 |
| West South Central | ar | faulkner | 280,500 | $129 | 2,168 |
| West South Central | ar | garland | 274,800 | $134 | 2,056 |
| West South Central | ar | jefferson | 314,600 | $144 | 2,179 |
| West South Central | ar | lonoke | 289,000 | $132 | 2,190 |
| West South Central | ar | pope | 273,200 | $114 | 2,389 |
| West South Central | ar | pulaski | 211,300 | $121 | 1,745 |
| West South Central | ar | saline | 273,500 | $114 | 2,396 |
| West South Central | ar | sebastian | 208,600 | $111 | 1,879 |
| West South Central | ar | washington | 215,600 | $126 | 1,712 |
| West South Central | ar | white | 254,800 | $145 | 1,763 |
| West South Central | la | acadia | 226,300 | $135 | 1,681 |
| West South Central | la | ascension | 303,200 | $149 | 2,030 |
| West South Central | la | bossier | 305,500 | $140 | 2,177 |
| West South Central | la | caddo | 278,500 | $158 | 1,768 |
| West South Central | la | calcasieu | 214,300 | $115 | 1,871 |
| West South Central | la | east baton rouge | 254,100 | $135 | 1,881 |
| West South Central | la | iberia | 188,700 | $125 | 1,511 |
| West South Central | la | jefferson | 306,100 | $131 | 2,344 |
| West South Central | la | lafayette | 221,000 | $108 | 2,040 |
| West South Central | la | lafourche | 297,000 | $128 | 2,320 |
| West South Central | la | livingston | 297,300 | $139 | 2,135 |
| West South Central | la | orleans | 258,600 | $152 | 1,698 |
| West South Central | la | ouachita | 304,300 | $158 | 1,921 |
| West South Central | la | rapides | 347,800 | $151 | 2,297 |
| West South Central | la | st. charles | 171,400 | $99 | 1,724 |
| West South Central | la | st. landry | 254,700 | $118 | 2,150 |
| West South Central | la | st. martin | 252,600 | $137 | 1,845 |
| West South Central | la | st. mary | 260,400 | $141 | 1,842 |
| West South Central | la | st. tammany | 280,300 | $150 | 1,869 |
| West South Central | la | tangipahoa | 242,300 | $110 | 2,202 |
| West South Central | la | terrebonne | 254,700 | $156 | 1,637 |
| West South Central | la | vermilion | 270,600 | $164 | 1,650 |
| West South Central | la | vernon | 255,900 | $113 | 2,256 |
| West South Central | ok | canadian | 218,000 | $95 | 2,290 |
| West South Central | ok | carter | 263,000 | $142 | 1,856 |
| West South Central | ok | cherokee | 302,100 | $167 | 1,809 |
| West South Central | ok | cleveland | 263,800 | $117 | 2,262 |
| West South Central | ok | comanche | 252,100 | $140 | 1,806 |
| West South Central | ok | creek | 362,200 | $157 | 2,305 |
| West South Central | ok | garfield | 220,300 | $132 | 1,670 |
| West South Central | ok | grady | 229,500 | $158 | 1,455 |
| West South Central | ok | le flore | 292,200 | $128 | 2,291 |
| West South Central | ok | muskogee | 206,400 | $125 | 1,646 |
| West South Central | ok | oklahoma | 219,000 | $121 | 1,804 |
| West South Central | ok | osage | 194,800 | $129 | 1,515 |
| West South Central | ok | payne | 272,200 | $124 | 2,204 |
| West South Central | ok | pottawatomie | 204,800 | $136 | 1,510 |
| West South Central | ok | rogers | 183,700 | $104 | 1,769 |
| West South Central | ok | tulsa | 295,000 | $130 | 2,267 |
| West South Central | ok | wagoner | 209,100 | $134 | 1,560 |
| West South Central | ok | washington | 167,100 | $110 | 1,526 |
| West South Central | tx | angelina | 270,200 | $172 | 1,568 |
| West South Central | tx | bastrop | 179,600 | $103 | 1,736 |
| West South Central | tx | bell | 323,100 | $143 | 2,262 |
| West South Central | tx | bexar | 260,800 | $111 | 2,359 |
| West South Central | tx | bowie | 223,600 | $153 | 1,463 |
| West South Central | tx | brazoria | 246,300 | $130 | 1,900 |
| West South Central | tx | brazos | 242,500 | $132 | 1,835 |
| West South Central | tx | cameron | 269,200 | $151 | 1,781 |
| West South Central | tx | collin | 374,700 | $161 | 2,325 |
| West South Central | tx | comal | 249,200 | $165 | 1,510 |
| West South Central | tx | coryell | 184,100 | $126 | 1,460 |
| West South Central | tx | dallas | 279,600 | $144 | 1,940 |
| West South Central | tx | denton | 254,500 | $124 | 2,052 |
| West South Central | tx | ector | 151,300 | $102 | 1,477 |
| West South Central | tx | el paso | 249,200 | $123 | 2,023 |
| West South Central | tx | ellis | 163,400 | $112 | 1,459 |
| West South Central | tx | fort bend | 222,800 | $114 | 1,958 |
| West South Central | tx | galveston | 296,100 | $139 | 2,127 |
| West South Central | tx | grayson | 248,700 | $135 | 1,837 |
| West South Central | tx | gregg | 188,200 | $112 | 1,679 |
| West South Central | tx | guadalupe | 263,800 | $146 | 1,804 |
| West South Central | tx | hardin | 283,500 | $152 | 1,867 |
| West South Central | tx | harris | 196,200 | $115 | 1,700 |
| West South Central | tx | harrison | 255,300 | $107 | 2,396 |
| West South Central | tx | hays | 230,000 | $154 | 1,490 |
| West South Central | tx | henderson | 285,700 | $122 | 2,343 |
| West South Central | tx | hidalgo | 224,600 | $121 | 1,853 |
| West South Central | tx | hood | 207,200 | $91 | 2,278 |
| West South Central | tx | hunt | 306,900 | $133 | 2,299 |
| West South Central | tx | jefferson | 213,500 | $99 | 2,154 |
| West South Central | tx | johnson | 234,900 | $115 | 2,040 |
| West South Central | tx | kaufman | 264,300 | $134 | 1,977 |
| West South Central | tx | kerr | 262,900 | $139 | 1,888 |
| West South Central | tx | liberty | 206,400 | $113 | 1,822 |
| West South Central | tx | lubbock | 476,700 | $133 | 3,583 |
| West South Central | tx | mclennan | 407,300 | $104 | 3,920 |
| West South Central | tx | midland | 515,000 | $141 | 3,648 |
| West South Central | tx | montgomery | 480,300 | $116 | 4,142 |
| West South Central | tx | nacogdoches | 630,800 | $124 | 5,107 |
| West South Central | tx | nueces | 496,200 | $115 | 4,310 |
| West South Central | tx | orange | 610,600 | $118 | 5,196 |
| West South Central | tx | parker | 727,900 | $122 | 5,962 |
| West South Central | tx | potter | 726,800 | $126 | 5,777 |
| West South Central | tx | randall | 476,700 | $90 | 5,284 |
| East South Central | al | autauga | 289,800 | $117 | 2,468 |
| East South Central | al | baldwin | 197,100 | $120 | 1,646 |
| East South Central | al | blount | 214,200 | $116 | 1,846 |
| East South Central | al | calhoun | 257,100 | $148 | 1,738 |
| East South Central | al | coffee | 297,200 | $129 | 2,295 |
| East South Central | al | colbert | 219,900 | $111 | 1,987 |
| East South Central | al | cullman | 239,500 | $121 | 1,978 |
| East South Central | al | dale | 317,500 | $123 | 2,579 |
| East South Central | al | elmore | 262,700 | $114 | 2,313 |
| East South Central | al | etowah | 167,700 | $71 | 2,372 |
| East South Central | al | houston | 263,700 | $103 | 2,549 |
| East South Central | al | jackson | 284,900 | $118 | 2,417 |
| East South Central | al | jefferson | 317,300 | $135 | 2,351 |
| East South Central | al | lauderdale | 291,600 | $137 | 2,130 |
| East South Central | al | lee | 291,100 | $162 | 1,792 |
| East South Central | al | limestone | 248,800 | $144 | 1,733 |
| East South Central | al | madison | 252,500 | $115 | 2,199 |
| East South Central | al | marshall | 233,700 | $134 | 1,743 |
| East South Central | al | mobile | 316,900 | $128 | 2,476 |
| East South Central | al | montgomery | 298,500 | $136 | 2,200 |
| East South Central | al | morgan | 285,500 | $134 | 2,133 |
| East South Central | al | russell | 207,400 | $124 | 1,679 |
| East South Central | al | shelby | 190,100 | $89 | 2,133 |
| East South Central | al | st. clair | 235,200 | $102 | 2,306 |
| East South Central | al | talladega | 203,500 | $113 | 1,800 |
| East South Central | al | tuscaloosa | 259,000 | $137 | 1,895 |
| East South Central | al | walker | 206,500 | $115 | 1,803 |
| East South Central | ky | boone | 325,000 | $142 | 2,290 |
| East South Central | ky | boyd | 213,600 | $102 | 2,104 |
| East South Central | ky | bullitt | 319,300 | $126 | 2,527 |
| East South Central | ky | campbell | 269,400 | $145 | 1,864 |
| East South Central | ky | christian | 325,600 | $136 | 2,390 |
| East South Central | ky | daviess | 239,800 | $113 | 2,118 |
| East South Central | ky | fayette | 227,800 | $109 | 2,085 |
| East South Central | ky | franklin | 272,400 | $112 | 2,432 |
| East South Central | ky | hardin | 223,600 | $133 | 1,675 |
| East South Central | ky | henderson | 311,400 | $127 | 2,460 |
| East South Central | ky | hopkins | 208,000 | $104 | 2,007 |
| East South Central | ky | jefferson | 265,900 | $117 | 2,279 |
| East South Central | ky | jessamine | 174,900 | $98 | 1,777 |
| East South Central | ky | kenton | 273,600 | $110 | 2,479 |
| East South Central | ky | laurel | 256,800 | $105 | 2,450 |
| East South Central | ky | madison | 265,400 | $135 | 1,960 |
| East South Central | ky | mccracken | 229,300 | $126 | 1,824 |
| East South Central | ky | oldham | 232,500 | $127 | 1,834 |
| East South Central | ky | pulaski | 234,200 | $117 | 2,003 |
| East South Central | ky | scott | 217,500 | $111 | 1,964 |
| East South Central | ky | warren | 279,300 | $158 | 1,773 |
| East South Central | ms | desoto | 288,300 | $118 | 2,438 |
| East South Central | ms | forrest | 254,800 | $111 | 2,295 |
| East South Central | ms | hancock | 336,800 | $143 | 2,357 |
| East South Central | ms | harrison | 281,200 | $130 | 2,158 |
| East South Central | ms | hinds | 268,600 | $106 | 2,532 |
| East South Central | ms | jackson | 179,400 | $92 | 1,947 |
| East South Central | ms | jones | 187,200 | $116 | 1,607 |
| East South Central | ms | lafayette | 295,100 | $119 | 2,482 |
| East South Central | ms | lamar | 251,400 | $142 | 1,770 |
| East South Central | ms | lauderdale | 275,800 | $134 | 2,063 |
| East South Central | ms | lee | 273,100 | $132 | 2,066 |
| East South Central | ms | lowndes | 283,400 | $155 | 1,827 |
| East South Central | ms | madison | 279,400 | $110 | 2,538 |
| East South Central | ms | oktibbeha | 264,400 | $124 | 2,135 |
| East South Central | ms | pearl river | 256,100 | $146 | 1,759 |
| East South Central | ms | rankin | 240,500 | $119 | 2,019 |
| East South Central | ms | warren | 191,100 | $105 | 1,826 |
| East South Central | tn | anderson | 329,700 | $138 | 2,389 |
| East South Central | tn | blount | 308,500 | $135 | 2,278 |
| East South Central | tn | bradley | 181,300 | $92 | 1,973 |
| East South Central | tn | carter | 293,000 | $126 | 2,328 |
| East South Central | tn | coffee | 174,700 | $93 | 1,887 |
| East South Central | tn | cumberland | 266,600 | $108 | 2,466 |
| East South Central | tn | davidson | 326,400 | $126 | 2,585 |
| East South Central | tn | dickson | 250,300 | $117 | 2,140 |
| East South Central | tn | greene | 226,000 | $116 | 1,950 |
| East South Central | tn | hamblen | 309,000 | $124 | 2,482 |
| East South Central | tn | hamilton | 303,200 | $136 | 2,232 |
| East South Central | tn | hawkins | 269,000 | $113 | 2,385 |
| East South Central | tn | jefferson | 264,900 | $129 | 2,048 |
| East South Central | tn | knox | 300,500 | $139 | 2,162 |
| East South Central | tn | loudon | 291,600 | $133 | 2,200 |
| East South Central | tn | madison | 292,500 | $167 | 1,756 |
| East South Central | tn | maury | 275,300 | $110 | 2,507 |
| East South Central | tn | mcminn | 234,900 | $108 | 2,176 |
| East South Central | tn | montgomery | 250,300 | $151 | 1,663 |
| East South Central | tn | putnam | 169,700 | $97 | 1,744 |
| East South Central | tn | roane | 217,200 | $129 | 1,690 |
| East South Central | tn | robertson | 305,600 | $134 | 2,281 |
| East South Central | tn | rutherford | 159,900 | $87 | 1,847 |
| East South Central | tn | sevier | 229,600 | $120 | 1,908 |
| East South Central | tn | sullivan | 207,500 | $104 | 1,996 |
| East South Central | tn | sumner | 544,400 | $117 | 4,666 |
| East South Central | tn | washington | 505,500 | $119 | 4,245 |
| East South Central | tn | williamson | 532,300 | $117 | 4,562 |
| East South Central | tn | wilson | 476,600 | $114 | 4,177 |
| East South Central | tn | madison | 564,900 | $99 | 5,719 |
| East South Central | ms | jones | 630,100 | $127 | 4,947 |
| East South Central | ms | lafayette | 605,300 | $115 | 5,248 |
| East South Central | al | talladega | 675,500 | $104 | 6,498 |
| East South Central | al | tuscaloosa | 633,100 | $107 | 5,894 |
| East South Central | al | jackson | 715,300 | $111 | 6,420 |
| Northeast | ny | albany | 297,400 | $207 | 1,439 |
| Northeast | ny | bronx | 314,100 | $207 | 1,515 |
| Northeast | ny | broome | 310,300 | $154 | 2,017 |
| Northeast | ny | cattaraugus | 372,600 | $179 | 2,077 |
| Northeast | ny | cayuga | 265,400 | $166 | 1,602 |
| Northeast | ny | chautauqua | 336,400 | $177 | 1,905 |
| Northeast | ny | chemung | 282,600 | $228 | 1,242 |
| Northeast | ny | clinton | 351,500 | $179 | 1,969 |
| Northeast | ny | columbia | 266,000 | $165 | 1,610 |
| Northeast | ny | cortland | 343,200 | $181 | 1,893 |
| Northeast | ny | dutchess | 298,300 | $175 | 1,708 |
| Northeast | ny | erie | 275,200 | $189 | 1,453 |
| Northeast | ny | franklin | 302,600 | $192 | 1,577 |
| Northeast | ny | fulton | 379,900 | $193 | 1,965 |
| Northeast | ny | genesee | 329,700 | $166 | 1,983 |
| Northeast | ny | herkimer | 306,900 | $171 | 1,797 |
| Northeast | ny | jefferson | 287,800 | $191 | 1,504 |
| Northeast | ny | kings | 247,900 | $189 | 1,310 |
| Northeast | ny | livingston | 353,400 | $220 | 1,603 |
| Northeast | ny | madison | 311,800 | $158 | 1,973 |
| Northeast | ny | monroe | 318,400 | $206 | 1,545 |
| Northeast | ny | montgomery | 259,300 | $156 | 1,658 |
| Northeast | ny | new york | 314,400 | $191 | 1,644 |
| Northeast | ny | niagara | 261,400 | $172 | 1,517 |
| Northeast | ny | oneida | 308,500 | $168 | 1,840 |
| Northeast | ny | onondaga | 307,300 | $179 | 1,714 |
| Northeast | ny | ontario | 295,800 | $186 | 1,594 |
| Northeast | ny | orange | 329,300 | $168 | 1,963 |
| Northeast | ny | oswego | 266,500 | $237 | 1,126 |
| Northeast | ny | otsego | 225,700 | $204 | 1,104 |
| Northeast | ny | putnam | 272,300 | $178 | 1,532 |
| Northeast | ny | rensselaer | 347,000 | $190 | 1,827 |
| Northeast | ny | richmond | 313,300 | $168 | 1,862 |
| Northeast | ny | rockland | 302,300 | $165 | 1,835 |
| Northeast | ny | saratoga | 304,600 | $157 | 1,946 |
| Northeast | ny | schenectady | 331,300 | $163 | 2,031 |
| Northeast | ny | st. lawrence | 256,900 | $148 | 1,734 |
| Northeast | ny | steuben | 270,600 | $191 | 1,416 |
| Northeast | ny | suffolk | 244,700 | $160 | 1,528 |
| Northeast | ny | tioga | 257,400 | $218 | 1,183 |
| Northeast | ny | tompkins | 238,000 | $142 | 1,678 |
| Northeast | ny | ulster | 228,600 | $162 | 1,407 |
| Northeast | ny | warren | 236,500 | $205 | 1,156 |
| Northeast | ny | washington | 257,300 | $203 | 1,265 |
| Northeast | ny | wayne | 321,300 | $204 | 1,573 |
| Northeast | ny | westchester | 330,000 | $159 | 2,072 |
| Northeast | pa | adams | 247,000 | $158 | 1,566 |
| Northeast | pa | allegheny | 224,200 | $196 | 1,145 |
| Northeast | pa | armstrong | 289,200 | $186 | 1,558 |
| Northeast | pa | beaver | 315,300 | $157 | 2,010 |
| Northeast | pa | berks | 207,400 | $173 | 1,199 |
| Northeast | pa | blair | 323,900 | $178 | 1,815 |
| Northeast | pa | bradford | 251,400 | $208 | 1,206 |
| Northeast | pa | bucks | 325,800 | $182 | 1,794 |
| Northeast | pa | cambria | 302,200 | $176 | 1,716 |
| Northeast | pa | carbon | 192,900 | $143 | 1,349 |
| Northeast | pa | centre | 290,200 | $184 | 1,574 |
| Northeast | pa | chester | 234,800 | $156 | 1,506 |
| Northeast | pa | clearfield | 257,900 | $170 | 1,517 |
| Northeast | pa | columbia | 277,800 | $174 | 1,595 |
| Northeast | pa | crawford | 292,400 | $204 | 1,435 |
| Northeast | pa | cumberland | 270,900 | $186 | 1,456 |
| Northeast | pa | dauphin | 282,800 | $140 | 2,025 |
| Northeast | pa | delaware | 242,100 | $184 | 1,315 |
| Northeast | pa | erie | 229,200 | $181 | 1,263 |
| Northeast | pa | fayette | 272,900 | $184 | 1,485 |
| Northeast | pa | franklin | 277,700 | $204 | 1,363 |
| Northeast | pa | indiana | 284,600 | $166 | 1,713 |
| Northeast | pa | lackawanna | 251,000 | $184 | 1,365 |
| Northeast | pa | lancaster | 248,500 | $170 | 1,465 |
| Northeast | pa | lawrence | 418,800 | $203 | 2,063 |
| Northeast | pa | lebanon | 377,800 | $201 | 1,881 |
| Northeast | pa | lehigh | 305,800 | $194 | 1,579 |
| Northeast | pa | luzerne | 386,500 | $186 | 2,077 |
| Northeast | pa | lycoming | 185,600 | $145 | 1,283 |
| Northeast | pa | mifflin | 309,500 | $164 | 1,888 |
| Northeast | pa | monroe | 414,000 | $199 | 2,085 |
| Northeast | pa | montgomery | 289,000 | $175 | 1,648 |
| Northeast | pa | northampton | 286,100 | $218 | 1,313 |
| Northeast | pa | northumberland | 301,600 | $163 | 1,852 |
| Northeast | pa | philadelphia | 246,700 | $166 | 1,489 |
| Northeast | pa | pike | 256,400 | $168 | 1,529 |
| Northeast | pa | schuylkill | 315,900 | $188 | 1,682 |
| Northeast | pa | somerset | 323,900 | $164 | 1,972 |
| Northeast | pa | venango | 284,800 | $163 | 1,749 |
| Northeast | pa | washington | 315,500 | $173 | 1,820 |
| Northeast | pa | york | 368,600 | $178 | 2,068 |
| Northeast | ny | richmond | 320,600 | $170 | 1,887 |
| Northeast | ny | rockland | 269,200 | $150 | 1,796 |
| Northeast | ny | saratoga | 277,300 | $151 | 1,842 |
| Northeast | ny | schenectady | 596,900 | $163 | 3,656 |
| Northeast | ny | st. lawrence | 507,400 | $142 | 3,583 |
| Northeast | ny | cattaraugus | 585,600 | $161 | 3,637 |
| Northeast | ny | cayuga | 523,300 | $167 | 3,141 |
| Northeast | ny | chautauqua | 532,600 | $144 | 3,697 |
| Northeast | ny | chemung | 614,600 | $153 | 4,022 |
| Northeast | pa | centre | 626,500 | $144 | 4,354 |
| Northeast | pa | chester | 786,800 | $149 | 5,290 |
| Northeast | pa | northumberland | 633,300 | $134 | 4,736 |
| Northeast | pa | philadelphia | 822,200 | $161 | 5,108 |
| West North Central | ia | black hawk | 286,700 | $204 | 1,404 |
| West North Central | ia | cerro gordo | 361,000 | $193 | 1,869 |
| West North Central | ia | clinton | 301,200 | $214 | 1,405 |
| West North Central | ia | dallas | 401,900 | $184 | 2,183 |
| West North Central | ia | dubuque | 331,100 | $180 | 1,839 |
| West North Central | ia | johnson | 421,400 | $195 | 2,165 |
| West North Central | ia | linn | 425,300 | $188 | 2,265 |
| West North Central | ia | polk | 393,600 | $192 | 2,048 |
| West North Central | ia | pottawattamie | 297,400 | $186 | 1,603 |
| West North Central | ia | scott | 286,600 | $191 | 1,501 |
| West North Central | ia | story | 395,000 | $170 | 2,325 |
| West North Central | ia | warren | 402,400 | $199 | 2,022 |
| West North Central | ia | woodbury | 245,500 | $139 | 1,761 |
| West North Central | ks | butler | 268,300 | $160 | 1,677 |
| West North Central | ks | douglas | 267,600 | $179 | 1,498 |
| West North Central | ks | johnson | 369,000 | $155 | 2,387 |
| West North Central | ks | leavenworth | 321,700 | $188 | 1,712 |
| West North Central | ks | reno | 402,000 | $196 | 2,052 |
| West North Central | ks | riley | 356,900 | $158 | 2,261 |
| West North Central | ks | saline | 245,200 | $142 | 1,721 |
| West North Central | ks | sedgwick | 303,400 | $194 | 1,563 |
| West North Central | ks | shawnee | 247,100 | $164 | 1,511 |
| West North Central | ks | wyandotte | 259,500 | $159 | 1,631 |
| West North Central | mn | anoka | 292,300 | $201 | 1,455 |
| West North Central | mn | blue earth | 315,900 | $208 | 1,518 |
| West North Central | mn | carver | 290,500 | $156 | 1,868 |
| West North Central | mn | chisago | 309,900 | $196 | 1,583 |
| West North Central | mn | clay | 350,900 | $163 | 2,158 |
| West North Central | mn | crow wing | 263,200 | $164 | 1,602 |
| West North Central | mn | dakota | 262,800 | $144 | 1,824 |
| West North Central | mn | goodhue | 340,200 | $148 | 2,296 |
| West North Central | mn | hennepin | 353,300 | $158 | 2,236 |
| West North Central | mn | olmsted | 211,000 | $148 | 1,427 |
| West North Central | mn | otter tail | 315,400 | $173 | 1,828 |
| West North Central | mn | ramsey | 344,400 | $166 | 2,073 |
| West North Central | mn | rice | 263,800 | $187 | 1,412 |
| West North Central | mn | scott | 426,800 | $181 | 2,361 |
| West North Central | mn | sherburne | 361,600 | $177 | 2,041 |
| West North Central | mn | st. louis | 337,200 | $163 | 2,066 |
| West North Central | mn | stearns | 362,000 | $163 | 2,223 |
| West North Central | mn | washington | 282,100 | $172 | 1,642 |
| West North Central | mn | winona | 270,600 | $149 | 1,816 |
| West North Central | mn | wright | 420,500 | $179 | 2,351 |
| West North Central | mo | boone | 418,900 | $179 | 2,341 |
| West North Central | mo | buchanan | 266,200 | $168 | 1,589 |
| West North Central | mo | cape girardeau | 292,100 | $162 | 1,798 |
| West North Central | mo | cass | 291,200 | $180 | 1,620 |
| West North Central | mo | christian | 351,600 | $197 | 1,786 |
| West North Central | mo | clay | 294,000 | $177 | 1,659 |
| West North Central | mo | cole | 408,200 | $187 | 2,183 |
| West North Central | mo | franklin | 310,900 | $143 | 2,173 |
| West North Central | mo | greene | 388,900 | $166 | 2,341 |
| West North Central | mo | jackson | 409,400 | $181 | 2,262 |
| West North Central | mo | jasper | 319,600 | $176 | 1,813 |
| West North Central | mo | jefferson | 324,000 | $183 | 1,766 |
| West North Central | mo | johnson | 371,300 | $155 | 2,388 |
| West North Central | mo | lincoln | 260,100 | $144 | 1,804 |
| West North Central | mo | newton | 322,600 | $146 | 2,205 |
| West North Central | mo | platte | 269,200 | $184 | 1,467 |
| West North Central | mo | saint louis city | 273,200 | $172 | 1,592 |
| West North Central | mo | st. charles | 309,400 | $143 | 2,158 |
| West North Central | mo | st. francois | 325,500 | $167 | 1,951 |
| West North Central | mo | st. louis | 387,900 | $195 | 1,994 |
| West North Central | mo | taney | 351,700 | $194 | 1,816 |
| West North Central | nd | burleigh | 345,300 | $162 | 2,132 |
| West North Central | nd | cass | 259,700 | $179 | 1,454 |
| West North Central | nd | grand forks | 390,700 | $173 | 2,258 |
| West North Central | nd | ward | 402,800 | $252 | 1,599 |
| West North Central | ne | buffalo | 471,600 | $197 | 2,393 |
| West North Central | ne | douglas | 324,500 | $162 | 2,006 |
| West North Central | ne | hall | 276,900 | $154 | 1,794 |
| West North Central | ne | lancaster | 354,400 | $149 | 2,379 |
| West North Central | ne | sarpy | 273,200 | $164 | 1,665 |
| West North Central | sd | lincoln | 461,000 | $195 | 2,359 |
| West North Central | sd | minnehaha | 414,900 | $217 | 1,908 |
| West North Central | sd | pennington | 233,600 | $146 | 1,600 |
| West North Central | mo | platte | 289,100 | $189 | 1,530 |
| West North Central | mo | saint louis city | 253,900 | $156 | 1,623 |
| West North Central | mo | st. charles | 430,300 | $187 | 2,302 |
| West North Central | mo | st. francois | 355,600 | $200 | 1,774 |
| West North Central | mo | st. louis | 440,100 | $197 | 2,229 |
| West North Central | mo | taney | 264,200 | $187 | 1,410 |
| West North Central | nd | burleigh | 428,200 | $178 | 2,400 |
| West North Central | nd | cass | 389,000 | $183 | 2,120 |
| West North Central | nd | grand forks | 394,400 | $169 | 2,338 |
| West North Central | nd | ward | 370,900 | $175 | 2,125 |
| West North Central | ne | buffalo | 360,800 | $152 | 2,375 |
| West North Central | ne | douglas | 278,700 | $191 | 1,458 |
| West North Central | ne | hall | 324,900 | $185 | 1,756 |
| West North Central | ne | lancaster | 300,700 | $191 | 1,574 |
| West North Central | ne | sarpy | 510,600 | $149 | 3,431 |
| West North Central | sd | lincoln | 543,800 | $158 | 3,431 |
| West North Central | sd | minnehaha | 623,500 | $162 | 3,854 |
| West North Central | ia | johnson | 643,300 | $160 | 4,021 |
| West North Central | ia | linn | 745,500 | $165 | 4,531 |
| West North Central | ia | polk | 720,300 | $162 | 4,459 |
| West North Central | ia | pottawattamie | 815,200 | $157 | 5,182 |
| West North Central | ia | scott | 869,200 | $151 | 5,774 |
| West North Central | ia | story | 930,400 | $178 | 5,223 |
| West North Central | ia | warren | 745,100 | $140 | 5,315 |
| Mid Atlantic | nj | atlantic | 214,600 | $173 | 1,239 |
| Mid Atlantic | nj | burlington | 309,600 | $169 | 1,833 |
| Mid Atlantic | nj | camden | 238,700 | $208 | 1,148 |
| Mid Atlantic | nj | cape may | 351,300 | $199 | 1,763 |
| Mid Atlantic | nj | cumberland | 314,800 | $260 | 1,209 |
| Mid Atlantic | nj | gloucester | 253,300 | $209 | 1,211 |
| Mid Atlantic | nj | hudson | 290,300 | $194 | 1,498 |
| Mid Atlantic | nj | hunterdon | 352,500 | $249 | 1,415 |
| Mid Atlantic | nj | mercer | 446,400 | $220 | 2,032 |
| Mid Atlantic | nj | monmouth | 278,800 | $241 | 1,159 |
| Mid Atlantic | nj | ocean | 316,000 | $156 | 2,028 |
| Mid Atlantic | nj | salem | 237,000 | $201 | 1,182 |
| Mid Atlantic | dc | district of columbia | 286,600 | $212 | 1,349 |
| Mid Atlantic | de | kent | 370,000 | $224 | 1,653 |
| Mid Atlantic | de | new castle | 343,700 | $179 | 1,921 |
| Mid Atlantic | de | sussex | 323,300 | $164 | 1,972 |
| Mid Atlantic | md | calvert | 302,200 | $198 | 1,529 |
| Mid Atlantic | md | carroll | 361,100 | $180 | 2,007 |
| Mid Atlantic | md | cecil | 357,700 | $201 | 1,779 |
| Mid Atlantic | md | charles | 309,700 | $154 | 2,012 |
| Mid Atlantic | md | frederick | 263,600 | $212 | 1,246 |
| Mid Atlantic | md | harford | 243,000 | $178 | 1,364 |
| Mid Atlantic | md | howard | 310,200 | $182 | 1,703 |
| Mid Atlantic | md | montgomery | 317,000 | $170 | 1,866 |
| Mid Atlantic | md | prince george's | 379,600 | $276 | 1,377 |
| Mid Atlantic | md | queen anne's | 273,400 | $190 | 1,436 |
| Mid Atlantic | md | st. mary's | 295,900 | $196 | 1,510 |
| Mid Atlantic | md | washington | 282,100 | $152 | 1,851 |
| Mid Atlantic | md | wicomico | 353,900 | $265 | 1,335 |
| Mid Atlantic | md | worcester | 274,400 | $226 | 1,215 |
| Mid Atlantic | md | allegany | 265,100 | $221 | 1,201 |
| Mid Atlantic | md | anne arundel | 355,200 | $183 | 1,942 |
| Mid Atlantic | md | baltimore | 311,800 | $162 | 1,921 |
| Mid Atlantic | md | baltimore city | 351,000 | $189 | 1,861 |
| Mid Atlantic | va | albemarle | 431,000 | $228 | 1,893 |
| Mid Atlantic | va | alexandria city | 357,200 | $214 | 1,673 |
| Mid Atlantic | va | arlington | 238,100 | $145 | 1,646 |
| Mid Atlantic | va | augusta | 336,700 | $206 | 1,638 |
| Mid Atlantic | va | bedford | 242,600 | $198 | 1,224 |
| Mid Atlantic | va | campbell | 372,000 | $218 | 1,703 |
| Mid Atlantic | va | charlottesville city | 310,800 | $187 | 1,662 |
| Mid Atlantic | va | chesapeake city | 343,400 | $221 | 1,555 |
| Mid Atlantic | va | chesterfield | 235,700 | $160 | 1,476 |
| Mid Atlantic | va | danville city | 272,400 | $192 | 1,417 |
| Mid Atlantic | va | fairfax | 390,100 | $214 | 1,826 |
| Mid Atlantic | va | fauquier | 254,100 | $219 | 1,162 |
| Mid Atlantic | va | franklin | 303,100 | $205 | 1,475 |
| Mid Atlantic | va | frederick | 274,900 | $189 | 1,453 |
| Mid Atlantic | va | hampton city | 267,200 | $156 | 1,716 |
| Mid Atlantic | va | hanover | 273,300 | $138 | 1,979 |
| Mid Atlantic | va | henrico | 248,100 | $171 | 1,451 |
| Mid Atlantic | va | henry | 361,200 | $260 | 1,390 |
| Mid Atlantic | va | james city | 271,300 | $209 | 1,296 |
| Mid Atlantic | va | loudoun | 259,000 | $179 | 1,450 |
| Mid Atlantic | va | lynchburg city | 346,400 | $180 | 1,922 |
| Mid Atlantic | va | montgomery | 277,500 | $247 | 1,122 |
| Mid Atlantic | va | newport news city | 296,900 | $178 | 1,667 |
| Mid Atlantic | va | norfolk city | 359,900 | $177 | 2,030 |
| Mid Atlantic | va | pittsylvania | 347,600 | $210 | 1,656 |
| Mid Atlantic | va | portsmouth city | 407,500 | $231 | 1,765 |
| Mid Atlantic | va | prince william | 294,100 | $144 | 2,036 |
| Mid Atlantic | va | richmond city | 339,800 | $177 | 1,915 |
| Mid Atlantic | va | roanoke | 348,200 | $170 | 2,054 |
| Mid Atlantic | va | roanoke city | 248,900 | $195 | 1,277 |
| Mid Atlantic | va | rockingham | 396,600 | $205 | 1,939 |
| Mid Atlantic | va | spotsylvania | 340,500 | $199 | 1,708 |
| Mid Atlantic | va | stafford | 306,800 | $153 | 2,007 |
| Mid Atlantic | va | suffolk city | 291,400 | $183 | 1,594 |
| Mid Atlantic | va | virginia beach city | 322,500 | $167 | 1,927 |
| Mid Atlantic | va | washington | 373,200 | $182 | 2,050 |
| Mid Atlantic | va | york | 320,900 | $171 | 1,878 |
| Mid Atlantic | md | prince george's | 317,100 | $166 | 1,906 |
| Mid Atlantic | md | queen anne's | 239,100 | $142 | 1,683 |
| Mid Atlantic | md | st. mary's | 292,400 | $150 | 1,948 |
| Mid Atlantic | md | washington | 222,100 | $164 | 1,356 |
| Mid Atlantic | md | wicomico | 339,100 | $172 | 1,973 |
| Mid Atlantic | md | worcester | 355,800 | $185 | 1,923 |
| Mid Atlantic | md | allegany | 329,100 | $192 | 1,716 |
| Mid Atlantic | md | anne arundel | 258,800 | $184 | 1,405 |
| Mid Atlantic | md | baltimore | 354,100 | $210 | 1,686 |
| Mid Atlantic | md | baltimore city | 241,400 | $170 | 1,419 |
| Mid Atlantic | va | albemarle | 381,800 | $207 | 1,845 |
| Mid Atlantic | va | alexandria city | 296,300 | $262 | 1,130 |
| Mid Atlantic | va | arlington | 323,700 | $245 | 1,322 |
| Mid Atlantic | va | portsmouth city | 279,900 | $165 | 1,696 |
| Mid Atlantic | va | prince william | 281,400 | $179 | 1,573 |
| Mid Atlantic | va | richmond city | 235,800 | $160 | 1,472 |
| Mid Atlantic | va | roanoke | 286,900 | $220 | 1,307 |
| Mid Atlantic | va | roanoke city | 265,400 | $228 | 1,163 |
| Mid Atlantic | va | rockingham | 313,400 | $210 | 1,490 |
| Mid Atlantic | va | spotsylvania | 574,800 | $166 | 3,463 |
| Mid Atlantic | nj | hudson | 444,400 | $140 | 3,168 |
| Mid Atlantic | nj | hunterdon | 459,300 | $142 | 3,237 |
| Mid Atlantic | nj | mercer | 456,100 | $139 | 3,288 |
| Mid Atlantic | nj | monmouth | 524,900 | $119 | 4,428 |
| Mid Atlantic | nj | ocean | 547,400 | $131 | 4,178 |
| Mid Atlantic | nj | salem | 535,300 | $133 | 4,020 |
| Mid Atlantic | dc | district of columbia | 690,000 | $132 | 5,227 |
| Mid Atlantic | de | kent | 580,600 | $116 | 4,985 |
| Mid Atlantic | de | new castle | 580,200 | $130 | 4,479 |
| South Atlantic | nc | alamance | 315,700 | $187 | 1,684 |
| South Atlantic | nc | beaufort | 411,900 | $190 | 2,163 |
| South Atlantic | nc | brunswick | 281,000 | $155 | 1,818 |
| South Atlantic | nc | buncombe | 446,000 | $204 | 2,190 |
| South Atlantic | nc | burke | 431,700 | $207 | 2,085 |
| South Atlantic | nc | cabarrus | 430,300 | $179 | 2,410 |
| South Atlantic | nc | caldwell | 255,900 | $160 | 1,604 |
| South Atlantic | nc | carteret | 313,200 | $146 | 2,147 |
| South Atlantic | nc | catawba | 329,700 | $149 | 2,215 |
| South Atlantic | nc | chatham | 322,200 | $200 | 1,611 |
| South Atlantic | nc | cleveland | 250,700 | $149 | 1,681 |
| South Atlantic | nc | craven | 312,500 | $192 | 1,626 |
| South Atlantic | nc | cumberland | 327,500 | $155 | 2,115 |
| South Atlantic | nc | davidson | 504,500 | $196 | 2,571 |
| South Atlantic | nc | durham | 335,300 | $153 | 2,191 |
| South Atlantic | nc | edgecombe | 349,400 | $170 | 2,061 |
| South Atlantic | nc | forsyth | 411,500 | $190 | 2,166 |
| South Atlantic | nc | franklin | 329,700 | $176 | 1,871 |
| South Atlantic | nc | gaston | 441,500 | $231 | 1,908 |
| South Atlantic | nc | granville | 380,700 | $189 | 2,019 |
| South Atlantic | nc | guilford | 256,700 | $147 | 1,745 |
| South Atlantic | nc | halifax | 360,800 | $147 | 2,447 |
| South Atlantic | nc | harnett | 447,900 | $225 | 1,992 |
| South Atlantic | nc | haywood | 298,000 | $169 | 1,760 |
| South Atlantic | nc | henderson | 413,400 | $162 | 2,555 |
| South Atlantic | nc | hoke | 305,700 | $152 | 2,011 |
| South Atlantic | nc | iredell | 413,600 | $203 | 2,034 |
| South Atlantic | nc | johnston | 390,700 | $172 | 2,276 |
| South Atlantic | nc | lee | 348,600 | $208 | 1,675 |
| South Atlantic | nc | lenoir | 399,900 | $173 | 2,309 |
| South Atlantic | nc | lincoln | 395,700 | $186 | 2,131 |
| South Atlantic | nc | mecklenburg | 363,300 | $158 | 2,304 |
| South Atlantic | nc | moore | 339,300 | $182 | 1,869 |
| South Atlantic | nc | nash | 333,200 | $190 | 1,758 |
| South Atlantic | nc | new hanover | 306,300 | $165 | 1,855 |
| South Atlantic | nc | onslow | 313,800 | $187 | 1,676 |
| South Atlantic | nc | orange | 488,300 | $227 | 2,151 |
| South Atlantic | ga | henry | 328,100 | $156 | 2,109 |
| South Atlantic | ga | houston | 355,300 | $154 | 2,306 |
| South Atlantic | ga | jackson | 368,900 | $172 | 2,148 |
| South Atlantic | ga | laurens | 275,900 | $163 | 1,694 |
| South Atlantic | ga | liberty | 325,100 | $187 | 1,734 |
| South Atlantic | ga | lowndes | 318,200 | $134 | 2,380 |
| South Atlantic | ga | muscogee | 339,700 | $164 | 2,076 |
| South Atlantic | ga | newton | 339,800 | $189 | 1,800 |
| South Atlantic | ga | paulding | 348,200 | $154 | 2,263 |
| South Atlantic | ga | richmond | 387,700 | $209 | 1,859 |
| South Atlantic | nc | union | 297,500 | $175 | 1,696 |
| South Atlantic | nc | wake | 399,800 | $169 | 2,368 |
| South Atlantic | nc | watauga | 438,700 | $182 | 2,405 |
| South Atlantic | nc | wayne | 357,100 | $195 | 1,831 |
| South Atlantic | nc | wilkes | 346,300 | $152 | 2,274 |
| South Atlantic | nc | wilson | 453,900 | $179 | 2,539 |
| South Atlantic | sc | aiken | 378,800 | $175 | 2,164 |
| South Atlantic | sc | beaufort | 314,400 | $149 | 2,107 |
| South Atlantic | sc | berkeley | 351,900 | $184 | 1,913 |
| South Atlantic | sc | charleston | 408,000 | $197 | 2,067 |
| South Atlantic | sc | cherokee | 374,100 | $183 | 2,046 |
| South Atlantic | sc | darlington | 362,900 | $205 | 1,769 |
| South Atlantic | sc | dorchester | 403,900 | $164 | 2,460 |
| South Atlantic | sc | florence | 404,900 | $187 | 2,166 |
| South Atlantic | sc | georgetown | 371,300 | $185 | 2,006 |
| South Atlantic | sc | horry | 443,300 | $206 | 2,154 |
| South Atlantic | sc | kershaw | 268,700 | $162 | 1,662 |
| South Atlantic | sc | lancaster | 439,000 | $180 | 2,439 |
| South Atlantic | sc | lexington | 378,600 | $199 | 1,903 |
| South Atlantic | sc | oconee | 331,000 | $150 | 2,210 |
| South Atlantic | sc | orangeburg | 305,400 | $172 | 1,780 |
| South Atlantic | sc | richland | 396,300 | $206 | 1,924 |
| South Atlantic | sc | spartanburg | 375,100 | $165 | 2,271 |
| South Atlantic | sc | sumter | 291,900 | $143 | 2,035 |
| South Atlantic | sc | york | 355,600 | $195 | 1,822 |
| South Atlantic | fl | alachua | 265,400 | $158 | 1,684 |
| South Atlantic | fl | bay | 309,700 | $169 | 1,830 |
| South Atlantic | fl | brevard | 413,700 | $170 | 2,437 |
| South Atlantic | fl | broward | 405,400 | $225 | 1,798 |
| South Atlantic | fl | charlotte | 474,900 | $188 | 2,520 |
| South Atlantic | fl | citrus | 284,200 | $177 | 1,606 |
| South Atlantic | fl | clay | 425,700 | $177 | 2,408 |
| South Atlantic | fl | collier | 413,800 | $178 | 2,322 |
| South Atlantic | fl | columbia | 376,300 | $180 | 2,095 |
| South Atlantic | fl | duval | 320,400 | $170 | 1,885 |
| South Atlantic | fl | escambia | 387,900 | $170 | 2,285 |
| South Atlantic | fl | flagler | 290,900 | $156 | 1,860 |
| South Atlantic | fl | hernando | 362,600 | $184 | 1,967 |
| South Atlantic | fl | highlands | 274,600 | $166 | 1,650 |
| South Atlantic | fl | hillsborough | 362,900 | $182 | 1,994 |
| South Atlantic | fl | indian river | 371,300 | $198 | 1,873 |
| South Atlantic | fl | lake | 348,200 | $180 | 1,931 |
| South Atlantic | fl | lee | 391,900 | $160 | 2,443 |
| South Atlantic | fl | leon | 619,200 | $147 | 4,213 |
| South Atlantic | fl | manatee | 707,400 | $178 | 3,985 |
| South Atlantic | fl | marion | 560,200 | $151 | 3,717 |
| South Atlantic | fl | martin | 592,000 | $151 | 3,919 |
| South Atlantic | fl | miami-dade | 792,900 | $165 | 4,810 |
| South Atlantic | fl | monroe | 854,400 | $173 | 4,929 |
| South Atlantic | fl | nassau | 736,100 | $133 | 5,517 |
| South Atlantic | fl | okaloosa | 879,200 | $142 | 6,196 |
| South Atlantic | fl | orange | 987,600 | $153 | 6,461 |
| South Atlantic | fl | osceola | 865,400 | $146 | 5,923 |
| Mountain | az | cochise | 381,000 | $189 | 2,018 |
| Mountain | az | coconino | 332,300 | $233 | 1,428 |
| Mountain | az | gila | 312,000 | $205 | 1,525 |
| Mountain | az | maricopa | 352,700 | $158 | 2,237 |
| Mountain | az | mohave | 471,000 | $225 | 2,097 |
| Mountain | az | navajo | 358,200 | $222 | 1,611 |
| Mountain | az | pima | 359,300 | $203 | 1,768 |
| Mountain | az | pinal | 314,800 | $223 | 1,413 |
| Mountain | az | yavapai | 319,000 | $140 | 2,280 |
| Mountain | az | yuma | 363,000 | $157 | 2,311 |
| Mountain | co | adams | 365,600 | $220 | 1,661 |
| Mountain | co | arapahoe | 257,500 | $170 | 1,513 |
| Mountain | co | boulder | 295,300 | $207 | 1,424 |
| Mountain | co | broomfield | 292,800 | $146 | 2,005 |
| Mountain | co | denver | 336,400 | $181 | 1,859 |
| Mountain | co | douglas | 387,000 | $162 | 2,383 |
| Mountain | co | eagle | 361,600 | $178 | 2,035 |
| Mountain | co | el paso | 270,500 | $158 | 1,713 |
| Mountain | co | garfield | 364,900 | $167 | 2,186 |
| Mountain | co | jefferson | 354,800 | $156 | 2,274 |
| Mountain | co | la plata | 434,700 | $202 | 2,151 |
| Mountain | co | larimer | 348,400 | $183 | 1,904 |
| Mountain | co | mesa | 300,700 | $168 | 1,792 |
| Mountain | co | pueblo | 305,700 | $167 | 1,830 |
| Mountain | co | weld | 382,600 | $178 | 2,151 |
| Mountain | id | ada | 402,600 | $174 | 2,309 |
| Mountain | id | bannock | 317,800 | $227 | 1,403 |
| Mountain | id | bonneville | 412,100 | $184 | 2,245 |
| Mountain | id | canyon | 295,600 | $155 | 1,903 |
| Mountain | id | kootenai | 308,700 | $184 | 1,675 |
| Mountain | id | twin falls | 319,000 | $169 | 1,892 |
| Mountain | mt | cascade | 296,000 | $126 | 2,341 |
| Mountain | mt | flathead | 309,300 | $155 | 1,998 |
| Mountain | mt | gallatin | 390,200 | $203 | 1,924 |
| Mountain | mt | lewis and clark | 287,300 | $187 | 1,533 |
| Mountain | mt | missoula | 370,300 | $177 | 2,091 |
| Mountain | mt | yellowstone | 326,000 | $198 | 1,643 |
| Mountain | nm | bernalillo | 378,000 | $196 | 1,926 |
| Mountain | nm | chaves | 390,200 | $204 | 1,915 |
| Mountain | nm | curry | 307,900 | $158 | 1,953 |
| Mountain | nm | dona ana | 319,400 | $148 | 2,160 |
| Mountain | nm | eddy | 383,900 | $185 | 2,071 |
| Mountain | nm | lea | 394,500 | $186 | 2,125 |
| Mountain | nm | mckinley | 386,500 | $169 | 2,290 |
| Mountain | nm | otero | 468,500 | $211 | 2,220 |
| Mountain | nm | san juan | 332,500 | $174 | 1,911 |
| Mountain | nm | sandoval | 434,600 | $190 | 2,283 |
| Mountain | nm | santa fe | 381,200 | $171 | 2,223 |
| Mountain | nm | valencia | 298,100 | $208 | 1,430 |
| Mountain | nv | carson city | 396,700 | $205 | 1,936 |
| Mountain | nv | clark | 274,100 | $193 | 1,419 |
| Mountain | nv | douglas | 414,000 | $174 | 2,375 |
| Mountain | nv | elko | 365,300 | $180 | 2,032 |
| Mountain | nv | lyon | 355,700 | $206 | 1,725 |
| Mountain | nv | washoe | 357,500 | $153 | 2,336 |
| Mountain | ut | cache | 278,900 | $185 | 1,509 |
| Mountain | ut | davis | 486,700 | $207 | 2,351 |
| Mountain | ut | salt lake | 304,300 | $185 | 1,645 |
| Mountain | ut | tooele | 311,300 | $199 | 1,568 |
| Mountain | ut | utah | 343,900 | $220 | 1,564 |
| Mountain | ut | washington | 370,500 | $209 | 1,770 |
| Mountain | ut | weber | 354,600 | $188 | 1,890 |
| Mountain | wy | laramie | 292,500 | $202 | 1,448 |
| Mountain | wy | natrona | 334,700 | $142 | 2,356 |
| Mountain | co | mesa | 308,200 | $163 | 1,890 |
| Mountain | co | pueblo | 225,200 | $154 | 1,462 |
| Mountain | co | weld | 299,200 | $212 | 1,412 |
| Mountain | id | ada | 315,500 | $142 | 2,222 |
| Mountain | id | bannock | 367,600 | $206 | 1,781 |
| Mountain | id | bonneville | 328,300 | $218 | 1,503 |
| Mountain | id | canyon | 279,800 | $178 | 1,572 |
| Mountain | id | kootenai | 351,300 | $229 | 1,536 |
| Mountain | id | twin falls | 415,500 | $177 | 2,349 |
| Mountain | mt | cascade | 309,800 | $194 | 1,598 |
| Mountain | mt | flathead | 336,000 | $185 | 1,813 |
| Mountain | mt | gallatin | 351,100 | $158 | 2,225 |
| Mountain | mt | lewis and clark | 299,500 | $176 | 1,702 |
| Mountain | mt | missoula | 355,600 | $187 | 1,901 |
| Mountain | mt | yellowstone | 311,200 | $199 | 1,564 |
| Mountain | az | maricopa | 389,700 | $172 | 2,270 |
| Mountain | az | mohave | 342,100 | $219 | 1,561 |
| Mountain | az | navajo | 339,000 | $177 | 1,916 |
| Mountain | az | pima | 393,900 | $225 | 1,751 |
| Mountain | az | pinal | 336,000 | $196 | 1,717 |
| Mountain | az | yavapai | 389,700 | $169 | 2,300 |
| Mountain | mt | gallatin | 348,800 | $244 | 1,431 |
| Mountain | mt | lewis and clark | 320,100 | $162 | 1,970 |
| Mountain | mt | missoula | 310,100 | $196 | 1,586 |
| Mountain | mt | yellowstone | 335,100 | $152 | 2,199 |
| Mountain | nm | bernalillo | 280,100 | $189 | 1,484 |
| Mountain | nm | chaves | 493,600 | $137 | 3,608 |
| Mountain | nm | curry | 528,000 | $142 | 3,720 |
| Mountain | nm | dona ana | 534,400 | $156 | 3,431 |
| Mountain | nm | eddy | 599,300 | $165 | 3,636 |
| Mountain | nm | lea | 588,700 | $118 | 4,995 |
| Mountain | nm | mckinley | 731,500 | $143 | 5,099 |
| Mountain | co | el paso | 539,600 | $126 | 4,273 |
| Mountain | co | garfield | 748,100 | $129 | 5,817 |
| Mountain | co | jefferson | 777,600 | $137 | 5,694 |
| Mountain | az | gila | 751,800 | $142 | 5,284 |
| New England | ct | fairfield | 364,100 | $149 | 2,444 |
| New England | ct | hartford | 342,500 | $175 | 1,956 |
| New England | ct | litchfield | 324,800 | $194 | 1,673 |
| New England | ct | middlesex | 347,000 | $157 | 2,214 |
| New England | ct | new haven | 329,000 | $163 | 2,013 |
| New England | ct | new london | 388,700 | $172 | 2,265 |
| New England | ct | tolland | 378,100 | $187 | 2,018 |
| New England | ct | windham | 415,600 | $161 | 2,584 |
| New England | ma | barnstable | 337,000 | $197 | 1,711 |
| New England | ma | berkshire | 422,800 | $168 | 2,511 |
| New England | ma | bristol | 362,400 | $214 | 1,695 |
| New England | ma | essex | 393,300 | $175 | 2,245 |
| New England | ma | franklin | 385,200 | $171 | 2,247 |
| New England | ma | hampden | 357,300 | $143 | 2,507 |
| New England | ma | hampshire | 258,800 | $153 | 1,686 |
| New England | ma | middlesex | 379,000 | $167 | 2,265 |
| New England | ma | norfolk | 313,400 | $174 | 1,806 |
| New England | ma | plymouth | 316,800 | $178 | 1,775 |
| New England | ma | suffolk | 358,600 | $153 | 2,346 |
| New England | ma | worcester | 395,800 | $176 | 2,246 |
| New England | me | androscoggin | 333,600 | $166 | 2,015 |
| New England | me | cumberland | 347,900 | $145 | 2,403 |
| New England | me | kennebec | 294,700 | $156 | 1,884 |
| New England | me | penobscot | 367,200 | $191 | 1,927 |
| New England | me | york | 306,100 | $174 | 1,762 |
| New England | nh | belknap | 357,600 | $178 | 2,013 |
| New England | nh | cheshire | 341,300 | $154 | 2,210 |
| New England | nh | grafton | 358,200 | $144 | 2,491 |
| New England | nh | hillsborough | 372,300 | $185 | 2,014 |
| New England | nh | merrimack | 340,300 | $198 | 1,715 |
| New England | nh | rockingham | 401,400 | $178 | 2,252 |
| New England | nh | strafford | 462,600 | $243 | 1,901 |
| New England | ri | bristol | 355,100 | $206 | 1,726 |
| New England | ri | kent | 375,800 | $175 | 2,145 |
| New England | ri | newport | 369,600 | $165 | 2,236 |
| New England | ri | providence | 386,100 | $154 | 2,511 |
| New England | ri | washington | 360,700 | $183 | 1,971 |
| New England | vt | chittenden | 340,300 | $183 | 1,855 |
| New England | vt | franklin | 330,300 | $183 | 1,807 |
| New England | vt | rutland | 393,600 | $154 | 2,552 |
| New England | vt | washington | 401,500 | $157 | 2,562 |
| New England | vt | windsor | 187,800 | $102 | 1,847 |
| New England | ct | fairfield | 299,700 | $167 | 1,798 |
| New England | ct | hartford | 338,000 | $147 | 2,293 |
| New England | ct | litchfield | 339,000 | $190 | 1,780 |
| New England | ct | middlesex | 368,400 | $194 | 1,900 |
| New England | ct | new haven | 387,100 | $181 | 2,142 |
| New England | ct | new london | 268,100 | $157 | 1,708 |
| New England | ct | tolland | 317,200 | $186 | 1,706 |
| New England | ct | windham | 381,900 | $154 | 2,475 |
| New England | ma | barnstable | 351,800 | $143 | 2,455 |
| New England | ma | berkshire | 346,200 | $150 | 2,310 |
| New England | ma | bristol | 441,000 | $199 | 2,214 |
| New England | ma | essex | 391,300 | $179 | 2,183 |
| New England | ma | franklin | 356,800 | $171 | 2,088 |
| New England | ma | hampden | 351,700 | $180 | 1,952 |
| New England | ma | hampshire | 316,500 | $180 | 1,755 |
| New England | ma | middlesex | 346,700 | $176 | 1,966 |
| New England | ma | norfolk | 394,600 | $202 | 1,949 |
| New England | ma | plymouth | 311,000 | $183 | 1,703 |
| New England | ma | suffolk | 423,600 | $170 | 2,491 |
| New England | ma | worcester | 346,000 | $213 | 1,622 |
| New England | me | androscoggin | 361,400 | $162 | 2,226 |
| New England | me | cumberland | 370,700 | $213 | 1,744 |
| New England | me | kennebec | 331,100 | $165 | 2,005 |
| New England | me | penobscot | 307,400 | $177 | 1,740 |
| New England | me | york | 370,000 | $186 | 1,991 |
| New England | nh | belknap | 397,300 | $181 | 2,196 |
| New England | nh | cheshire | 331,400 | $128 | 2,588 |
| New England | nh | grafton | 373,800 | $175 | 2,131 |
| New England | nh | hillsborough | 331,300 | $190 | 1,744 |
| New England | nh | merrimack | 305,500 | $166 | 1,843 |
| New England | nh | rockingham | 395,000 | $168 | 2,358 |
| New England | nh | strafford | 363,700 | $185 | 1,969 |
| New England | ri | bristol | 377,100 | $181 | 2,079 |
| New England | ri | kent | 397,900 | $165 | 2,405 |
| New England | ri | newport | 338,300 | $199 | 1,697 |
| New England | ri | providence | 344,100 | $208 | 1,654 |
| New England | ri | washington | 416,200 | $162 | 2,565 |
| New England | vt | chittenden | 257,600 | $130 | 1,981 |
| New England | vt | franklin | 341,300 | $180 | 1,892 |
| New England | vt | rutland | 344,200 | $151 | 2,280 |
| New England | vt | washington | 353,200 | $167 | 2,120 |
| New England | vt | windsor | 293,800 | $182 | 1,614 |
| New England | nh | strafford | 349,800 | $171 | 2,045 |
| New England | ri | bristol | 305,000 | $174 | 1,748 |
| New England | ri | kent | 283,700 | $164 | 1,732 |
| New England | ri | newport | 402,200 | $157 | 2,556 |
| New England | ri | providence | 379,100 | $148 | 2,566 |
| New England | ri | washington | 357,800 | $181 | 1,975 |
| New England | vt | chittenden | 560,900 | $136 | 4,128 |
| New England | vt | franklin | 489,900 | $131 | 3,747 |
| New England | vt | rutland | 523,600 | $126 | 4,162 |
| New England | vt | washington | 534,800 | $124 | 4,327 |
| New England | vt | windsor | 731,000 | $137 | 5,319 |
| New England | ma | middlesex | 791,100 | $151 | 5,230 |
| New England | ma | norfolk | 803,400 | $142 | 5,660 |
| New England | ma | plymouth | 814,300 | $125 | 6,516 |
| New England | ma | suffolk | 853,700 | $143 | 5,987 |
| New England | ma | worcester | 844,500 | $136 | 6,204 |
| Pacific | ak | anchorage | 450,000 | $259 | 1,739 |
| Pacific | ak | fairbanks north star | 330,600 | $231 | 1,430 |
| Pacific | ak | matanuska-susitna | 431,500 | $273 | 1,583 |
| Pacific | ca | alameda | 472,100 | $229 | 2,065 |
| Pacific | ca | butte | 406,200 | $217 | 1,875 |
| Pacific | ca | contra costa | 366,500 | $225 | 1,626 |
| Pacific | ca | el dorado | 388,400 | $211 | 1,839 |
| Pacific | ca | fresno | 389,500 | $279 | 1,395 |
| Pacific | ca | humboldt | 349,500 | $234 | 1,494 |
| Pacific | ca | imperial | 343,900 | $233 | 1,478 |
| Pacific | ca | kern | 364,800 | $236 | 1,546 |
| Pacific | ca | kings | 408,100 | $246 | 1,656 |
| Pacific | ca | lake | 335,700 | $235 | 1,430 |
| Pacific | ca | los angeles | 393,100 | $219 | 1,793 |
| Pacific | ca | madera | 439,800 | $275 | 1,597 |
| Pacific | ca | marin | 420,800 | $227 | 1,856 |
| Pacific | ca | mendocino | 478,200 | $237 | 2,020 |
| Pacific | ca | merced | 339,600 | $197 | 1,726 |
| Pacific | ca | monterey | 417,200 | $344 | 1,213 |
| Pacific | ca | napa | 404,100 | $228 | 1,769 |
| Pacific | ca | nevada | 377,400 | $234 | 1,614 |
| Pacific | ca | orange | 354,800 | $322 | 1,101 |
| Pacific | ca | placer | 314,600 | $266 | 1,182 |
| Pacific | ca | riverside | 329,500 | $259 | 1,274 |
| Pacific | ca | sacramento | 291,500 | $176 | 1,655 |
| Pacific | ca | san bernardino | 465,500 | $249 | 1,873 |
| Pacific | ca | san diego | 421,400 | $202 | 2,081 |
| Pacific | ca | san francisco | 413,100 | $259 | 1,595 |
| Pacific | ca | san joaquin | 468,200 | $225 | 2,083 |
| Pacific | ca | san luis obispo | 370,000 | $297 | 1,246 |
| Pacific | ca | san mateo | 314,300 | $210 | 1,500 |
| Pacific | ca | santa barbara | 355,600 | $269 | 1,323 |
| Pacific | ca | santa clara | 329,000 | $261 | 1,262 |
| Pacific | ca | santa cruz | 405,100 | $207 | 1,955 |
| Pacific | ca | shasta | 344,900 | $298 | 1,157 |
| Pacific | ca | solano | 343,700 | $277 | 1,240 |
| Pacific | ca | sonoma | 381,400 | $229 | 1,663 |
| Pacific | ca | stanislaus | 389,300 | $272 | 1,431 |
| Pacific | ca | sutter | 354,600 | $255 | 1,390 |
| Pacific | ca | tehama | 371,200 | $232 | 1,597 |
| Pacific | ca | tulare | 403,900 | $258 | 1,566 |
| Pacific | ca | tuolumne | 367,700 | $227 | 1,619 |
| Pacific | ca | ventura | 373,300 | $244 | 1,532 |
| Pacific | ca | yolo | 516,300 | $270 | 1,914 |
| Pacific | ca | yuba | 424,000 | $216 | 1,959 |
| Pacific | hi | hawaii | 437,000 | $222 | 1,970 |
| Pacific | hi | honolulu | 273,300 | $224 | 1,220 |
| Pacific | hi | kauai | 512,300 | $252 | 2,030 |
| Pacific | hi | maui | 342,000 | $298 | 1,149 |
| Pacific | or | benton | 351,000 | $294 | 1,192 |
| Pacific | or | clackamas | 401,700 | $226 | 1,780 |
| Pacific | or | columbia | 367,800 | $244 | 1,509 |
| Pacific | or | coos | 399,800 | $259 | 1,542 |
| Pacific | or | deschutes | 351,500 | $240 | 1,467 |
| Pacific | or | douglas | 357,000 | $270 | 1,324 |
| Pacific | or | jackson | 301,200 | $191 | 1,581 |
| Pacific | or | josephine | 491,900 | $266 | 1,847 |
| Pacific | or | klamath | 387,200 | $254 | 1,526 |
| Pacific | or | lane | 404,600 | $219 | 1,845 |
| Pacific | or | lincoln | 371,200 | $278 | 1,334 |
| Pacific | or | linn | 392,200 | $283 | 1,386 |
| Pacific | or | marion | 419,300 | $217 | 1,936 |
| Pacific | or | multnomah | 385,500 | $223 | 1,728 |
| Pacific | or | polk | 298,400 | $235 | 1,271 |
| Pacific | or | umatilla | 467,100 | $254 | 1,841 |
| Pacific | or | washington | 296,800 | $223 | 1,329 |
| Pacific | or | yamhill | 458,800 | $227 | 2,020 |
| Pacific | wa | benton | 443,000 | $247 | 1,790 |
| Pacific | wa | chelan | 367,500 | $231 | 1,591 |
| Pacific | wa | clallam | 427,000 | $204 | 2,096 |
| Pacific | wa | clark | 460,700 | $240 | 1,922 |
| Pacific | wa | cowlitz | 420,400 | $227 | 1,856 |
| Pacific | wa | franklin | 436,000 | $250 | 1,744 |
| Pacific | wa | grant | 370,100 | $274 | 1,351 |
| Pacific | wa | grays harbor | 395,300 | $284 | 1,393 |
| Pacific | wa | island | 269,300 | $213 | 1,263 |
| Pacific | wa | king | 405,700 | $225 | 1,800 |
| Pacific | wa | kitsap | 362,900 | $249 | 1,459 |
| Pacific | wa | lewis | 402,300 | $219 | 1,841 |
| Pacific | wa | mason | 332,900 | $291 | 1,145 |
| Pacific | wa | pierce | 500,200 | $251 | 1,993 |
| Pacific | wa | skagit | 330,100 | $277 | 1,193 |
| Pacific | wa | snohomish | 356,400 | $257 | 1,385 |
| Pacific | wa | spokane | 422,800 | $289 | 1,462 |
| Pacific | wa | thurston | 309,400 | $239 | 1,296 |
| Pacific | wa | walla walla | 420,400 | $214 | 1,963 |
| Pacific | wa | whatcom | 430,400 | $256 | 1,680 |
| Pacific | wa | whitman | 362,200 | $293 | 1,238 |
| Pacific | wa | yakima | 442,800 | $259 | 1,709 |
| Pacific | or | umatilla | 345,500 | $313 | 1,104 |
| Pacific | or | washington | 764,900 | $218 | 3,504 |
| Pacific | or | yamhill | 676,100 | $185 | 3,656 |
| Pacific | wa | benton | 615,800 | $174 | 3,530 |
| Pacific | wa | chelan | 611,400 | $197 | 3,099 |
| Pacific | wa | clallam | 887,800 | $201 | 4,422 |
| Pacific | ca | tuolumne | 789,800 | $182 | 4,334 |
| Pacific | ca | ventura | 654,300 | $182 | 3,597 |
| Pacific | ca | yolo | 859,000 | $171 | 5,019 |
| Pacific | ca | yuba | 777,900 | $168 | 4,635 |
| Pacific | hi | hawaii | 856,600 | $174 | 4,927 |
course_documents/MAT 240 Downloading Excel Tutorial.pdf
Downloading Excel Tutorial
Overview One of the many benefits of being a student at SNHU is that you are eligible to download Word, Excel, PowerPoint, Outlook, OneNote, Publisher, and Access on up to 5 PCs or Macs and Office apps on other mobile devices including Windows tablets and iPads®. The plan also includes 1TB of OneDrive storage, managed by the school, and students can edit and collaborate using Office Online, Yammer, and SharePoint sites. Please note the following:
• Students can use the plan until you graduate or are no longer enrolled at a qualified school. Student eligibility may be re-verified at any time.
• To install Office 365, your PC or Mac must meet the minimum system requirements
In this course you will need to use Microsoft Word and Microsoft Excel to complete your assignments. If you do not already have these programs on your device, follow the directions below to download them.
Installation 1. Navigate to office365.com in your internet browser and log in using your SNHU credentials. 2. Select the “Install Office” button on the top right of the screen.
a. It is suggested you select “Office 365 apps” for a simple download experience. 3. Review the directions in the pop-up window “Just a Few More Steps”, and then follow the
download prompts as they appear.
Please note that you are also able to use Microsoft Office products such as Word, Excel, and PowerPoint within the Microsoft Office Portal site without needing to download the software, however these versions have limited features and capabilities.
- Downloading Excel Tutorial
- Overview
- Installation
course_documents/MAT 240 Random Sampling in Excel Tutorial.pdf
MAT 240 Random Sampling in Excel Tutorial This tutorial will guide you though the steps necessary to collect a random sample of a data set to put on a new sheet.
1. Open your data set in Excel. Be sure the Analysis toolpak is enabled. Steps for how to do this are available on the Microsoft support site.
2. To find a random sample, you first need to insert the =rand() function an empty column next to your data. In the example being shown, it is column G. To do this, select the target cell and type in =rand() then press enter.
3. Double click the Fill handle (little square icon) at the bottom right side of the highlighted cell to copy the formula through to the bottom of the data set. This will copy this formula to each row
of data.
4. Sort your new column to rearrange the data into a random order. To do this, select the data within your column, then click the Sort & Filter button from the Home ribbon and choose Sort
Smallest to Largest.
5. A dialog box will open asking if you what you want to do. Select to Expand the selection and click Sort.
6. Capture your sample size by selecting the amount of rows you are sampling. A sample of 50 would mean you should select the first 50 rows of data.
a. By selecting only the first cell of data in the first column and dragging down, Excel will count the number of rows for you.
b. Once you have the correct number of rows, then drag to the right to highlight all the data in the appropriate number of rows.
7. Cut and paste this selected data set onto a new sheet and you will have your random sample separated from the main data set.
8. In the Descriptive statistics window, select input range field, then select all your numerical data
9. Then check the Summary Statistics box and click ok
10. You now should see a new sheet with just your descriptive statistics listed in a chart. Change the titles of the columns to their respective names from your data: median listing price, median dollars per square foot, median square feet. And remove any extraneous information that is not needed for this project.
- MAT 240 Random Sampling in Excel Tutorial
course_documents/MAT 240 Scatterplots in Excel Tutorial.pdf
MAT 240 Scatterplots in Excel Tutorial
This tutorial will guide you through the steps necessary to create scatterplots using your data. It will also walk you through inserting a linear trend line and inserting the regression equation and the R-squared value on the chart.
1. Open your data set in Excel.
2. Select all the data for the two variables you are targeting (e.g., median listing price and median square feet).
Tip: Holding down the Ctrl key while selecting your data will allow you to select two columns of data that are not next to each other.
3. On the Insert tab, click the Recommended Charts button.
This will bring up the Insert Chart dialog box, which prompts you to select from the list of auto-generated charts. If Scatter is not one of the options, click the All Charts tab. Then select X Y (Scatter) and select the chart on the right side. Click OK.
4. With the new chart selected, go to the Chart Design tab and click the Add Chart Element button. In the drop-down menu, hover over Trendline and select More Trendline Options.
5. In the Format Trendline sidebar, select Linear. At the bottom, check the boxes for these options:
Display Equation on Chart Display R-Squared Value on Chart
6. Close the Format Trendline sidebar and move the equation and R-squared value to the side so that it is visible.
Tip: You can use an empty cell to have Excel calculate the square root of your R-squared value by selecting an empty cell in your sheet and using the =sqrt() function.
Type your R-squared value into the parenthesis and hit enter.
- MAT 240 Scatterplots in Excel Tutorial
course_documents/MAT 240 Descriptive Statistics in Excel.pdf
MAT 240 Descriptive Statistics in Excel This tutorial will guide you through the steps necessary to pull out the descriptive statistics of your data using the Analysis TookPak. If you do not have the Office 365 version of Excel, download the latest version. (See the Downloading Office 365 Programs tutorial linked in your Brightspace course.) 1. Open your data set in Excel. Be sure the Analysis ToolPak is enabled. Steps for how to do this are
available on the Microsoft Support site. 2. On the Data tab, click the Data Analysis button.
3. The Data Analysis window includes a list of analysis tools. Select Descriptive Statistics from the list
and click OK.
4. In the Descriptive Statistics box, select the Input Range field. Then select all your numerical data.
5. Check the box next to Summary Statistics and click OK.
6. You should see a new sheet with just your descriptive statistics listed in a chart. Change the titles of
the columns to their respective names from your data. Remove any information that is not needed for this project.
course_documents/MAT 240 Creating Histograms in Excel.pdf
MAT 240 Creating Histograms in Excel This tutorial will guide you through the steps necessary to create histograms from your data. Since you have two variables for this data set, you will need to create two histograms—one for each variable.
1. Open your data set in Excel. Be sure the Analysis ToolPak is enabled. Steps for how to do this are available on the Microsoft Support site.
2. Select all the data for one variable. 3. On the Insert tab, click Recommended Charts.
4. This will bring up the Insert Chart dialog box, which prompts you to select from a list of auto-generated charts. If Histogram is not one of the options, select the All Charts tab and click Histogram. Then click OK.
5. Repeat the previous steps for your second variable’s data.
- MAT 240 Creating Histograms in Excel