Project help
Hallouma@22
2 years ago
20
files (3)ProjectInstructions.docx
FinalProjectSummaryReportTemplate1.docx
crime1.csv
ProjectInstructions.docx
Context of data
This dataset compiles crime records from 51 states, featuring a condensed set of fields that center around key attributes like the unemployment rate, single parent rate, college-educated people rate, and more. Your role as a data analyst is to compute the crime rate for each state by leveraging the specified attributes in the dataset. Apply your understanding of both simple and multiple linear regression analysis, acquired in our class, to predict the crime rate effectively.
FinalProjectSummaryReportTemplate1.docx
BSTAT 3321 Final Project Summary Report
[Full Name]
[UTA Email]
The University of Texas at Arlington
Notes:
· Replace the bracketed text on page one (the cover page) with your personal information.
1. Introduction
Discuss the statement of the problem in terms of the statistical analyses that are being performed. Be sure to address the following:
What is the data set that you are exploring?
How will your results be used?
What type of analyses will you be running in this project?
Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include R code in your report.
2. Data Preparation
1. What are the variables stored in crime.csv? ( use the following functions for R)
crime <- read.csv("crime.csv")
str(crime))
Answer the questions in a paragraph response. Remove all questions and this note before submitting! Do not include R code in your report.
3. Simple Linear Regression: Create a simple linear regression model to predict the murder rate using single.parent.
In general, how is a simple linear regression model used to predict the response variable using the predictor variable?
What is the equation for your model?
Report the P-value in a formatted table as shown below:
|
Statistic |
Value |
|
P-value |
X.XXXX *Round off to 4 decimal places. |
What is the predicted murder rate for a state that has single.paren of 25.4? Round your answer down to the nearest integer.
Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include R code in your report.
2. Multiple Regression: Create a multiple linear regression model to predict the murder rate using all important variables.
In general, how is a multiple linear regression model used to predict the response variable using predictor variables?
Report the P-value in a formatted table as shown below:
|
Statistic |
Value |
|
P-value |
X.XXXX *Round off to 4 decimal places. |
Based on the results of the overall p- value, is at least one of the predictors statistically significant in predicting the murder rate?
List all the important variables to predict the murder rate based on p-value.
Report and interpret the coefficient of determination.
What is the equation for your model?
What is the predicted murder rate based on your final multiple regression model (assume some random values for your variables)?
Answer the questions in a paragraph response. Remove all questions and this note (but not the table) before submitting! Do not include R code in your report.
3. Conclusion
Describe the results of the statistical analyses clearly, using proper descriptions of statistical terms and concepts. Fully describe what these results mean for your scenario.
Briefly summarize your findings in plain language.
What is the practical importance of the analyses that were performed?
4. Citations
You were not required to use external resources for this report. If you did not use any resources, you should remove this entire section. However, if you did use any resources to help you with your interpretation, you must cite them. Use proper APA format for citations.
Insert references here in the following format:
Author's Last Name, First Initial. Middle Initial. (Year of Publication). Title of book: Subtitle of book, edition. Place of Publication: Publisher.
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crime1.csv
| murder.rate | poverty | high.school | college | single.parent | unemployed | metropolitan |
| 7.4 | 14.7 | 77.5 | 20.4 | 26 | 4.6 | 70.2 |
| 4.3 | 8.4 | 90.4 | 28.1 | 23.2 | 6.6 | 41.6 |
| 7 | 13.5 | 85.1 | 24.6 | 23.5 | 3.9 | 87.9 |
| 6.3 | 15.8 | 81.7 | 18.4 | 24.7 | 4.4 | 49 |
| 6.1 | 14 | 81.2 | 27.5 | 21.8 | 4.9 | 96.7 |
| 3.1 | 8.5 | 89.7 | 34.6 | 20.8 | 2.7 | 84 |
| 2.9 | 7.7 | 88.2 | 31.6 | 22.9 | 2.3 | 95.6 |
| 3.2 | 9.9 | 86.1 | 24 | 25.6 | 4 | 81.4 |
| 5.6 | 12 | 84 | 22.8 | 26.5 | 3.6 | 93 |
| 8 | 12.5 | 82.6 | 23.1 | 25.5 | 3.7 | 69.1 |
| 2.9 | 10.6 | 87.4 | 26.3 | 19.1 | 4.3 | 72.9 |
| 1.2 | 13.3 | 86.2 | 20 | 17.7 | 4.9 | 38.6 |
| 7.2 | 10.5 | 85.5 | 27.1 | 21.9 | 4.4 | 84.5 |
| 5.8 | 8.3 | 84.6 | 17.1 | 22.8 | 3.2 | 71.8 |
| 1.6 | 7.9 | 89.7 | 25.5 | 19.8 | 2.6 | 44.9 |
| 6.3 | 10.5 | 88.1 | 27.3 | 20.2 | 3.7 | 56.8 |
| 4.8 | 12.5 | 78.7 | 20.5 | 23.2 | 4.1 | 48.4 |
| 12.5 | 18.5 | 80.8 | 22.5 | 29.3 | 5.5 | 75.2 |
| 1.2 | 9.8 | 89.3 | 24.1 | 23.7 | 3.5 | 36.3 |
| 8.1 | 7.3 | 85.7 | 32.3 | 24.5 | 3.9 | 92.7 |
| 2 | 10.2 | 85.1 | 32.7 | 22.8 | 2.6 | 92.1 |
| 6.7 | 10.2 | 86.2 | 23 | 24.5 | 3.6 | 82.5 |
| 3.1 | 7.9 | 90.8 | 31.2 | 19.6 | 3.3 | 70.3 |
| 9 | 15.5 | 80.3 | 18.7 | 30 | 5.7 | 36.2 |
| 6.2 | 9.8 | 86.6 | 26.2 | 24.3 | 3.5 | 68 |
| 1.8 | 16 | 89.6 | 23.8 | 21.4 | 4.9 | 33.4 |
| 3.7 | 10.7 | 90.4 | 24.6 | 19.6 | 3 | 52.2 |
| 6.5 | 10.1 | 82.8 | 19.3 | 24.2 | 4.1 | 86.6 |
| 1.8 | 7.6 | 88.1 | 30.1 | 20 | 2.8 | 60.3 |
| 3.4 | 8.1 | 87.3 | 30.1 | 20.2 | 3.8 | 100 |
| 7.4 | 19.3 | 82.2 | 23.6 | 26.6 | 4.9 | 57 |
| 5 | 14.7 | 82.5 | 28.7 | 26 | 4.6 | 91.9 |
| 7 | 13.2 | 79.2 | 23.2 | 24.3 | 3.6 | 67.2 |
| 0.6 | 12.8 | 85.5 | 22.6 | 19.1 | 3 | 43.4 |
| 3.7 | 11.1 | 87 | 24.6 | 24.6 | 4.1 | 80.9 |
| 5.3 | 14.1 | 86.1 | 22.5 | 23.5 | 3 | 60.6 |
| 2 | 12.9 | 88.1 | 27.2 | 22.5 | 4.9 | 72.8 |
| 4.9 | 9.8 | 85.7 | 24.3 | 22.8 | 4.2 | 84.5 |
| 4.3 | 10.2 | 81.3 | 26.4 | 27.4 | 4.1 | 93.8 |
| 5.8 | 12 | 83 | 19 | 27.1 | 3.9 | 70.2 |
| 0.9 | 9.4 | 91.8 | 25.7 | 20.7 | 2.3 | 34.5 |
| 7.2 | 13.4 | 79.9 | 22 | 27.9 | 3.9 | 67.9 |
| 5.9 | 14.9 | 79.2 | 23.9 | 21.5 | 4.2 | 84.6 |
| 1.9 | 8.1 | 90.7 | 26.4 | 13.6 | 3.2 | 76.4 |
| 1.5 | 10.3 | 90 | 28.8 | 22.5 | 2.9 | 27.9 |
| 5.7 | 8.1 | 86.6 | 31.9 | 22.2 | 2.2 | 78.2 |
| 3.3 | 9.5 | 91.8 | 28.6 | 22.1 | 5.2 | 83 |
| 2.5 | 15.8 | 77.1 | 15.3 | 22.3 | 5.5 | 41.9 |
| 3.2 | 9 | 86.7 | 23.8 | 21.7 | 3.5 | 67.8 |
| 2.4 | 11.1 | 90 | 20.6 | 20.8 | 3.9 | 29.6 |
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