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Sun_Descriptive_Numerical_Analysis_Start.xlsx

Instructions

Descriptive Numerical Analysis
Project Description:
The present study investigates the distribution of sale prices for homes in a region in upstate New York. This project will also seek to compare the distributions of sale prices between homes with central air and homes without central air. Suppose you are being transferred to this area and are interested in getting a good description of selling prices for homes in this region. The variables collected in the data are: Price: Recorded in dollars; Lot size: measured in acres; Living Area: measured in square feet; Pct College: percent of students going to college; Central Air: No – 0, Yes – 1; Bedrooms: Number of bedrooms; Fireplace: Number of fireplaces; Bathrooms: Number of bathrooms. For the purpose of this project, you will only be using the variables Price and Central Air.
Instructions:
Use a cell reference or a single formula where appropriate in order to receive full credit. Do not copy and paste values or type values, as you will not receive full credit for your answers. For the purpose of grading the project you are required to perform the following tasks:
Step Instructions Points Possible
1 Start Excel. Download and open the workbook named: 0
Descriptive_Numerical_Analysis_Start
2 Obtain the descriptive statistics for sale prices for all homes in the dataset. 8
Adding Descriptive Statistics
Go to the Data worksheet. Select Data Analysis in the Analysis group of the Data tab of the Ribbon (note you should add this Add-in in case you do not have it in the Data tab already). Select Descriptive Statistics and click OK. Select the Price column as the Input Range. Choose Grouped by Columns. Check the ‘Labels in the first row’ box. Choose cell I1 on the Data worksheet as the output range. Check the ‘Summary statistics’ box. Do not check any additional boxes in the Descriptive Statistics menu.
In cell I16 on the Data worksheet, type Q1. In cell J16, calculate the value of the first quartile for the Price data set.
In cell I17 on the Data worksheet, type Q3. In cell J17, calculate the value of the third quartile for the Price data set.
In cells D7-D14 on the Problem worksheet, identify the values for the mean, standard deviation, minimum, first quartile, median, third quartile, maximum, and sample size. Round the monetary values to the nearest cent.
3 In cell D18, identify the range of sales prices. 1
4 In cell D19, calculate the size of the bins for 25 bins. 1
5 To construct the histogram, first create a column of ‘bins’ on the Data worksheet. Since the bin size is not a round number in thousands of dollars, choose the bin size to be 30,000. In cell K1 on the Data worksheet, type Binsize. In cell K2, type 30000, in cell K3, type 60000, and then drag the sequence down until you pass the most expensive selling price. 4
Now construct the histogram.
Inserting the Histogram
On the Data worksheet, select Data Analysis in the Analysis group of the Data tab of the Ribbon. Select Histogram and click OK. Select the Price column as the Input Range and the Binsize column (starting on cell K1) as the Bin Range. Check the ‘Labels’ box. Choose cell M1 on the Data worksheet as the output range. Check the ‘Chart Output’ box. Do not check any additional boxes in the Descriptive Statistics menu.
Moving the Histogram
Select the Histogram. Then choose Move Chart in the Design tab on the Ribbon. Select the Problem worksheet in the provided drop-down menu. Drag the histogram on the Problem worksheet and change its size so that it is located in cell C23.
Edit Chart Elements
Change the title of the histogram to Distribution of selling prices. Right click on one of the bars and select ‘Format Data Series’. Slide the ‘Gap Width’ to zero.
6 In cells F26-G26, choose how you would describe the shape of the distribution from the drop-down menu. 1
7 In cells F27-G27, choose which measure of 'center' is best to describe the distribution from the drop-down menu. 1
8 In cells F28-G28, choose how to compare the values of the mean and the median from the drop-down menu. 1
9 In cells F29-G29, choose which measure of 'spread' is best to describe the distribution from the drop-down menu. 1
10 In cell D34, calculate the percentage of homes rounded to one decimal place whose prices are expected to exceed $300,000 using the value(s) found in step 5. Note: Using the Histogram tool, a value is included in a particular bin if the number is greater than the lowest bound and equal to or less than the greatest bound for the data bin. 1
11 In cell D36, calculate the percentage of homes rounded to one decimal place that are priced between $90,000 and $300,001, exclusive, using the value(s) found in step 5. Note: Using the Histogram tool, a value is included in a particular bin if the number is greater than the lowest bound and equal to or less than the greatest bound for the data bin. 1
12 In cell D38, calculate the percentage of homes rounded to one decimal place expected to be priced less than or equal to $150,000 using the value(s) found in step 5. Note: Using the Histogram tool, a value is included in a particular bin if the number is greater than the lowest bound and equal to or less than the greatest bound for the data bin. 1
13 Construct two histograms showing the distribution of prices for homes without central air and the prices for homes with central air. 8
First, create the two columns of data. On the Data worksheet, copy the Price column to columns P and Q. In cell P1, type Price without central air. In cell Q1, type Price with central air. Then select the first row, go to the Home tab of the Ribbon, and select Sort&Filter in the Editing group. Select Filter in the drop-down menu. In cell E1, open the drop-down menu and select to show only value 0. Delete all of the filtered values in column Q. Then in cell E1 in the drop-down menu, select to show only value 1. Delete all of the filtered values in column P. Go back to cell E1 and select to show all values.
Construct the histogram using Data Analysis for the Price without central air column using the Binsize column K (starting on cell K1). Choose cell R1 on the Data worksheet as the output range. Be sure to check the ‘Labels’ and ‘Chart Output’ boxes in the Histogram menu. Move the histogram to the Problem worksheet and place it in cells B42-C42. Change the title of the histogram to Distribution of selling prices without central air. Right click on one of the bars and select ‘Format Data Series’. Slide the ‘Gap Width’ to zero.
Construct the histogram using Data Analysis for the Price with central air column using the Binsize column K (starting on cell K1). Choose cell T1 on the Data worksheet as the output range. Be sure to check the ‘Labels’ and ‘Chart Output’ boxes in the Histogram menu. Move the histogram to the Problem worksheet and place it in cells D42-G42. Change the title of the histogram to Distribution of selling prices with central air. Right click on one of the bars and select ‘Format Data Series’. Slide the ‘Gap Width’ to zero.
14 Obtain the descriptive statistics for sale prices for homes without central air. Go to the Data worksheet and use Descriptive Statistics in Data Analysis for the Price without central air column. Choose cell V1 on the Data worksheet as the output range. Be sure to check the ‘Labels in the first row’ and ‘Summary statistics’ boxes. 7
In cell V16 on the Data worksheet, type Q1. In cell W16, calculate the value of the first quartile for the Price without central air data set.
In cell V17 on the Data worksheet, type Q3. In cell W17, calculate the value of the third quartile for the Price without central air data set.
In cells E45-E51 on the Problem worksheet, identify the values for the minimum, first quartile, median, mean, third quartile, maximum, and sample size. Round the monetary values to the nearest cent.
15 Obtain the descriptive statistics for sale prices for homes with central air. Go to the Data worksheet and use Descriptive Statistics in Data Analysis for the Price with central air column. Choose cell X1 on the Data worksheet as the output range. Be sure to check the ‘Labels in the first row’ and ‘Summary statistics’ boxes. 7
In cell X16 on the Data worksheet, type Q1. In cell Y16, calculate the value of the first quartile for the Price with central air data set.
In cell X17 on the Data worksheet, type Q3. In cell Y17, calculate the value of the third quartile for the Price with central air data set.
In cells E45-E51 on the Problem worksheet, identify the values for the minimum, first quartile, median, mean, third quartile, maximum, and sample size. Round the monetary values to the nearest cent.
16 In cells D55 and D56, compare the estimated sale prices of homes with central air to homes without central air. Choose the correct answers from the drop-down menus. 7
In cell E58, calculate the expected difference in median costs. In cells D60, F60, D61, and F61, identify the variability of prices using Q1 and Q3 for each data set. Use the descriptive statistics in cells D45-E51. Keep the same number of decimal places as the values in step14 and step15.
17 Save the workbook. Close the workbook and then exit Excel. Submit the workbook as directed. 0
Total Score 50

Problem

Problem Housing Data
The present study investigates the distribution of sale prices for homes in a region in upstate New York and to compare the distributions of sale prices between homes with central air and homes without central air. Suppose you are being transferred to this area and are interested in getting a good description of selling prices for homes there. Use a cell reference or a single formula where appropriate in order to receive full credit. Do not copy and paste values or type values, as you will not receive full credit for your answers.
1-2) Obtain the descriptive statistics for sale prices for all homes in the dataset. Provide the values below:
Identify the mean sale price to the nearest cent in cell D7.
Identify the standard deviation of the sale prices to the nearest cent in D8.
Identify the minimum sale price to the nearest cent in cell D9.
Identify the first quartile sale price to the nearest cent in cell D10.
Identify the median sale price to the nearest cent in cell D11.
Identify the third quartile sale price to the nearest cent in cell D12.
Identify the maximum sale price to the nearest cent in cell D13.
Identify the sample size in cell D14.
To begin to construct the histogram of sale prices, we need to determine our bins. These are the upper limits to the size of the bars on the x-axis. We do this by calculating the range of the prices, and dividing by the number of bars we want in our histogram. Since we have a large sample size, let us choose to have about 25 bins.
3) Identify the range of sale prices in cell D18.
4) Calculate the size of the bins for 25 bins in cell D19.
5) Construct the histogram using the bins calculated. Follow the directions in step5 in the instructions document. Insert the histogram in cell C23.
Describe the distribution of housing prices of homes in upstate New York.
6) In cells F26-G26, choose how you would describe the shape of the distribution from the drop-down menu.
7) In cells F27-G27, choose which measure of 'center' is best to describe the distribution from the drop-down menu.
8) In cells F28-G28, choose how to compare the values of the mean and the median from the drop-down menu.
9) In cells F29-G29, choose which measure of 'spread' is best to describe the distribution from the drop-down menu.
Use the histogram (or the grouped frequency distribution) to answer the following.
10) In cell D34, calculate the percentage of homes rounded to one decimal place whose prices are expected to exceed $300,000 using the value(s) found in step 5.
11) In cell D36, calculate the percentage of homes rounded to one decimal place that are priced between $90,000 and $300,001, exclusive, using the value(s) found in step 5.
12) In cell D38, calculate the percentage of homes rounded to one decimal place expected to be priced less than or equal to $150,000 using the value(s) found in step 5.
13) Suppose you are looking at two houses in the same neighborhood that are about the same size except one of the homes has central air and the other one does not. Compare the distributions for homes with central air and homes without central air. Find the five-number-summary measures for homes with central air and for homes without central air.
Using the same bins you used in question 3), construct separate histograms for the sale prices for homes without central air and the sale prices for homes with central air. Title each histogram so that they are labeled appropriately by central air status. Insert the two histograms in cells B42-G42.
14-15) Obtain the descriptive statistics for sale prices for homes without central air and with central air in the dataset. Provide the values below. Round the monetary values to the nearest cent.
Without Central Air With Central Air
Minimum sale price, in cells D45 and E45
Q1, in cells D46 and E46
Median, in cells D47 and E47
Mean, in cells D48 and E48
Q3, in cells D49 and E49
Maximum, in cells D50 and E50
n, sample size, in cells D51 and E51
16) Write a brief summary statement comparing the sale prices of homes with and without central air using the medians and the interquartile ranges as a general range of prices one would expect to pay for 'typical' homes in this region of upstate New York using the statements provided below.
In cells D55 and D56, compare the estimated sale prices of homes with central air to homes without central air. Choose the correct answers from the drop-down menus.
Homes with central air generally sell for prices than homes without central air.
This is indicated by comparing the home prices between homes with and without central air.
Calculate the expected difference in median costs in cell E58. Keep the same number of decimal places as the values in step14 and step15.
Given this data, one would estimate that homes with central air can be expected to cost about more than homes without central air.
Identify the variability of prices using Q1 and Q3 for each data set in cells D60, F60, D61, and F61. Keep the same number of decimal places as the values in step14 and step15.
The variability of prices for the typical home without central air ranges from about to
as compared to to for homes with central air.

Data

Price Lot Size Living Area Pct College Central Air Bedrooms Fireplaces Bathrooms
132500 0.09 906 35 0 2 1 1
181115 0.92 1953 51 0 3 0 2.5
109000 0.19 1944 51 0 4 1 1
155000 0.41 1944 51 0 3 1 1.5
86060 0.11 840 51 1 2 0 1
120000 0.68 1152 22 0 4 1 1
153000 0.4 2752 51 0 4 1 1.5
170000 1.21 1662 35 0 4 1 1.5
90000 0.83 1632 51 0 3 0 1.5
122900 1.94 1416 44 0 3 0 1.5
325000 2.29 2894 51 0 7 0 1
120000 0.92 1624 51 0 3 0 2
85860 8.97 704 41 0 2 0 1
97000 0.11 1383 57 0 3 0 2
127000 0.14 1300 41 0 3 0 1.5
89900 0 936 57 0 3 0 1
155000 0.13 1300 41 0 3 0 1.5
253750 2 2816 71 1 4 1 2.5
60000 0.21 924 35 0 2 0 1
87500 0.88 1092 35 0 3 0 1
112000 1 1056 35 0 3 0 1
104900 0.43 1600 39 0 3 0 1.5
148635 0.32 1576 39 1 3 0 2.5
150000 0.03 2080 39 0 3 0 2
90400 0.36 1600 39 0 3 0 1.5
248800 4 2224 39 0 4 0 3
135000 1.83 1656 39 0 3 0 1
145000 3 1170 39 0 4 0 1.5
457000 0.43 2461 39 0 4 1 2
140000 0.44 1544 71 1 3 1 1.5
130000 1.24 1220 71 0 2 2 1
187000 0.46 1858 52 0 3 1 2.5
229000 0.87 2219 64 0 3 1 2
227000 1.8 1876 52 0 3 0 2.5
179900 0.46 2026 52 0 4 1 2.5
169900 0.91 1671 71 1 4 1 3
209900 0.46 2060 52 0 4 1 2.5
169900 0.59 1884 52 0 4 1 2.5
293000 7.24 2022 71 0 4 2 3
245900 0.19 2394 71 1 4 1 2.5
157000 0.46 1390 71 0 3 1 1.5
195000 0.41 1954 71 1 4 0 2.5
150000 0.78 1554 71 1 3 1 1.5
234900 0.89 1976 64 1 3 0 2.5
279550 1.34 2479 71 0 4 1 2.5
246500 1 2714 71 0 4 1 2.5
124000 1 797 52 0 2 0 1
138000 0.27 1500 71 0 3 0 2.5
290000 0.71 1838 71 0 4 0 2
108000 0.9 1042 71 0 2 1 2
134900 0.24 1782 52 1 3 0 2.5
64500 0.06 1480 52 0 2 1 2.5
142000 0.55 1426 52 0 3 1 2
125000 0.34 1404 52 0 3 0 2
88000 0.19 1480 52 1 3 1 1.5
135000 0.23 1344 52 0 3 0 1
90000 0.07 1480 52 1 2 1 2.5
90100 0.09 1480 52 0 3 1 1.5
126900 0.25 1596 52 0 3 0 2.5
175000 0.47 1768 52 0 3 1 2
158000 0.36 1348 52 1 2 1 2
92000 0.07 1480 52 0 3 1 1.5
82800 0.11 1483 52 0 3 0 1
140000 0.23 1576 52 1 4 1 1.5
171000 3.16 1008 52 0 2 0 1
200640 0.08 2332 52 0 4 0 2.5
139000 0.57 1064 52 0 3 1 1
225000 0.5 2428 52 1 4 1 2.5
182000 1 1310 52 0 3 1 2
208767 0.5 1662 52 1 3 0 2
186000 0.55 2000 52 0 4 0 2.5
93000 0.1 1480 52 0 3 1 1.5
257386 0.5 2969 52 1 4 1 4
161000 0.31 1542 52 1 3 0 2.5
92000 0.28 1527 52 0 4 0 2
211002 0.06 2195 52 0 4 0 2.5
115000 0.06 1480 52 0 3 1 1.5
113000 0.46 1452 52 1 3 0 2
216300 0.1 2360 52 0 4 0 2.5
145000 2.12 1440 52 0 3 1 1
114000 0.06 1480 52 0 2 1 2.5
139050 0.21 1879 52 0 3 0 2.5
104000 0.06 1480 52 0 3 0 1.5
169900 0.26 1792 52 0 3 0 2.5
177900 0.29 1386 44 0 3 0 2.5
133000 1.29 1676 44 1 2 1 2
185000 1 768 22 0 4 0 2
115000 0.88 1560 22 1 3 1 1.5
100000 0.52 1000 22 0 3 0 1
117000 0.07 1676 51 0 4 1 1.5
150000 0.32 1656 51 0 3 0 1.5
187500 0.92 2300 51 0 3 1 1.5
107000 0.46 1712 51 0 3 1 1
126900 0.46 1350 51 0 3 0 1.5
147000 0.11 1676 51 0 3 1 2.5
62000 0.4 1317 51 0 3 0 1.5
101000 0.87 1056 51 0 3 1 2
143500 0.59 912 51 0 3 0 1
113400 0.93 1232 44 0 2 0 2
76320 0.15 1380 44 0 3 1 1
110000 0.59 936 44 1 3 0 1
88000 0.33 720 44 0 3 0 1
108000 0.32 1628 44 0 2 1 1.5
114900 0.46 1144 44 0 3 0 1.5
146000 0.48 1827 44 0 3 0 2.5
225000 2.37 1784 44 0 3 1 2
138000 0.83 1851 44 1 3 1 2.5
218070 1 2194 44 0 4 0 2.5
25000 0.21 920 44 0 2 0 1
112000 0.27 1280 44 0 3 0 1
112500 0.72 1232 44 0 3 1 1
97000 0.36 1406 44 0 3 0 1.5
121000 0.52 1164 44 0 3 0 2
65720 0.19 1198 44 0 3 0 1
225000 0.38 2206 44 1 4 1 2.5
192000 0.82 1880 44 1 3 1 2.5
158500 0.69 1368 44 0 3 0 1.5
247000 0.51 1901 44 1 3 1 2.5
193777 0.72 1547 44 0 3 0 2
136500 0.62 896 44 0 3 0 2
75000 1 1008 44 0 3 0 1
45000 0.52 912 44 0 2 0 1
243000 0.82 2443 44 0 3 0 2.5
90000 0.29 900 44 0 4 0 1
158000 0.52 2098 44 1 3 0 2
174000 0.64 2115 44 0 4 1 2.5
150000 0.52 1344 44 0 2 1 2
159650 1 1106 44 0 3 0 1
139062 0.69 1440 44 0 3 2 2
84950 0.13 840 51 0 2 0 1
102000 0.22 1170 51 0 2 0 1
175000 0.46 1664 51 0 4 0 1
78500 1 3024 51 0 4 0 1
232478 1 2598 51 0 4 1 2.5
93805 0.13 840 51 0 2 0 1.5
119900 1.03 1701 41 0 5 0 1
146000 1.17 1456 41 0 3 1 1.5
125000 0.34 1224 71 0 3 0 1
135000 0.38 1411 71 0 3 1 1
157500 1.96 1608 71 0 3 1 1.5
135000 3 3020 41 0 4 0 2.5
142900 0.33 1898 64 0 3 1 1.5
259900 0.46 2544 64 1 4 1 2.5
85000 0.29 1038 64 0 2 0 1
180377 0.35 1820 64 0 3 1 2.5
163500 0.28 2202 64 1 3 1 2
106500 0.52 2387 64 0 3 0 1
115000 0.11 1368 64 1 2 1 1.5
115000 0.14 1480 64 1 2 1 2
135000 0.14 1348 64 1 2 1 1.5
198900 0.47 1889 64 1 4 1 2.5
139000 0.14 1343 64 1 2 1 1.5
206000 0.51 2011 64 1 3 1 2.5
120000 0.21 1180 64 1 2 1 1.5
205980 0.14 1983 64 1 3 1 2.5
275000 0.55 2253 64 1 3 1 2.5
139000 0.07 1604 64 1 2 0 1.5
89900 0.49 1196 45 0 3 0 1
139900 0.07 1602 64 1 2 0 2.5
172750 0.36 1747 64 0 3 0 2.5
136000 0.5 1092 64 0 3 0 1
270000 0.48 2410 64 1 4 1 2.5
174000 0.29 1933 64 1 3 1 2.5
379000 0.68 3080 64 1 4 1 2.5
382500 4.08 4534 64 1 6 2 2.5
144900 0.1 1677 64 1 3 1 2.5
349900 0.62 2900 64 1 4 1 2.5
133000 0.07 1392 64 1 2 1 1.5
115000 0.16 1058 64 0 2 1 1.5
211950 0.36 2342 64 1 4 1 2.5
227812 0.01 2206 64 1 4 1 2.5
164400 0.34 1516 64 1 3 1 2
340000 0.75 2836 64 1 4 1 2.5
139900 0.29 1256 64 1 2 0 1.5
279900 0.47 2340 64 1 4 1 3.5
225000 0.32 2129 64 1 4 1 2.5
144500 0.12 1343 64 1 2 1 2.5
362710 1 2963 64 1 4 1 2.5
247000 0.46 2114 64 1 4 1 3.5
120000 0.18 1144 64 1 2 1 1
136000 0.55 988 64 0 3 1 1
228500 0.46 1475 64 0 3 0 2
162800 0.15 1247 64 0 3 0 1.5
230000 0.93 1912 64 0 5 1 2
115800 0.46 1440 64 0 3 0 1.5
175000 0.26 1596 64 1 3 1 2
263008 0.63 2665 64 1 4 1 2.5
146000 0.5 1984 64 0 3 0 1.5
204900 0.03 1616 64 1 3 0 2
265000 0.17 1917 64 0 3 1 2.5
167500 0.64 2592 64 0 3 1 1.5
205000 0.47 1845 64 0 3 1 2.5
170000 0.92 1360 57 1 4 0 1
176000 0.41 1664 64 1 3 1 1.5
132000 0.16 1098 64 1 2 1 1.5
115500 0.01 1214 64 0 2 0 1.5
150000 0.29 1046 57 0 3 0 1
120000 0.36 1144 64 0 3 0 1
125000 0.28 1140 64 1 2 1 2
150000 0.15 1232 64 0 2 1 1.5
362360 0.59 3020 64 1 4 1 2.5
133500 0.36 1508 52 0 3 1 2
91000 0.16 912 52 0 2 1 1.5
104000 0.34 1508 52 0 3 0 1.5
148000 0.33 1561 52 0 3 1 1.5
182000 0.56 2625 64 0 4 1 2.5
152500 0.48 936 52 0 3 1 1
97000 0.16 912 52 0 2 0 1.5
113000 0.17 1492 52 0 3 0 2.5
172000 0.46 1599 64 0 4 1 2.5
179900 0.81 2304 52 0 5 1 2.5
84000 0.15 912 52 0 2 0 1.5
117900 0.15 1385 52 1 2 1 1.5
177000 0.32 1561 52 0 4 0 1.5
107500 0.16 884 52 0 2 0 2
92500 0.15 912 52 0 2 0 2
102900 0.15 912 52 0 2 0 1.5
134800 0.48 1384 52 0 3 0 2
150000 0.77 1334 52 0 3 0 1.5
165000 0.42 1433 64 1 3 1 2
120000 0.17 1492 52 0 3 1 2.5
177500 0.32 1561 52 1 4 1 1.5
300000 0.09 936 52 0 1 0 1
123500 0.16 1492 52 0 3 1 2.5
141000 0.16 1853 52 0 3 0 2.5
105400 0.15 1240 52 0 2 0 1.5
100600 0.17 912 52 0 2 0 1.5
108900 0.17 912 52 0 2 0 1.5
105500 0.16 912 52 0 2 0 1.5
109900 0.16 1184 52 0 3 0 1.5
172700 0.34 1638 52 0 3 1 2
166500 0.31 1508 52 0 3 1 2
105000 0.4 672 52 0 2 0 1
490000 0.34 1346 52 0 3 1 2
120000 0.16 1184 52 0 3 0 2
107500 0.15 912 52 0 2 0 1.5
116600 0.15 912 52 0 2 1 1.5
65000 0.16 988 52 0 2 0 2
118000 0.16 1184 52 0 3 0 2
115900 0.15 1385 52 0 2 0 1.5
100000 0.15 912 52 0 2 0 1.5
171000 0.37 1548 52 1 3 1 2
188000 0.31 1561 52 0 4 0 1.5
140000 1 1008 52 1 2 0 1
124500 0.15 1385 52 0 2 0 1.5
107200 0.16 908 52 0 2 0 1
107500 0.24 2246 39 0 4 0 1.5
180000 2.06 1820 39 0 3 1 2.5
214325 0.42 2554 64 1 4 1 2.5
128850 0.92 824 45 0 3 0 1.5
208700 0.4 2458 64 0 4 1 2.5
139900 0.36 1324 64 0 3 0 1
350000 5.84 2916 64 1 3 1 2.5
108000 0.16 1032 52 0 2 0 1.5
115500 0.15 912 52 0 2 1 1.5
135000 0.98 1320 52 0 2 0 1
135000 0.33 1508 52 0 3 1 1.5
107400 0.16 912 52 0 2 1 1.5
233000 0.09 2040 52 1 4 1 2.5
105000 0.16 912 52 0 2 1 1.5
335000 3 1776 52 1 2 0 2
139000 0.58 1304 64 0 3 0 2
209500 0.42 1836 64 1 4 1 2.5
101000 0.17 912 52 0 2 0 2
77500 0.16 912 52 0 2 0 1.5
150500 0.31 1527 52 0 2 1 2
167000 0.99 1454 39 0 3 0 1.5
114000 0.26 1700 39 0 3 1 1.5
160000 0.45 1680 45 0 4 0 1
85000 0.49 2401 64 1 4 1 2.5
143000 0.35 1176 64 0 3 0 1
126000 0.4 1344 64 0 3 1 1.5
140000 0.48 1344 64 0 3 0 1.5
140000 0.35 1714 64 0 3 0 2.5
205000 0.25 1992 64 0 4 1 3
79900 0.12 924 64 1 2 0 1
139000 0.09 1290 64 1 2 1 1.5
190000 0.46 2521 64 0 4 1 2.5
151500 0.71 1377 82 0 3 1 1.5
97500 0.06 1237 64 1 2 1 1.5
194500 0.61 2310 64 1 4 1 2.5
195160 0.32 1863 64 0 3 1 2.5
152500 0.37 1693 64 1 3 1 1.5
159500 0.29 1684 64 1 3 1 2.5
185000 0.95 1585 64 1 3 1 1.5
240000 0.67 2290 64 1 4 1 3
187900 0.4 2464 64 1 5 1 2.5
262000 0.29 2549 64 1 4 1 2.5
212500 0.35 2316 64 1 4 1 2.5
220000 0.37 2600 64 1 4 1 2.5
245000 0.53 2677 64 1 4 1 2.5
120000 0.06 1479 64 1 3 0 1.5
102500 0.15 1138 64 1 2 0 1
136000 0.27 1576 64 0 3 0 2.5
212500 0.43 2084 82 1 4 1 2.5
205900 0.06 1726 64 1 3 1 2
259900 1 1851 71 1 2 2 2
191500 0.46 2310 64 0 5 1 2.5
272500 0.03 2930 64 0 4 1 2.5
191500 0.88 2576 64 0 4 1 2.5
158000 0.55 1664 64 0 3 1 2
195000 1 1237 64 0 2 0 1.5
187500 0.43 2662 64 1 5 1 2.5
160000 0.45 1575 64 0 3 1 1.5
137500 0.1 1566 64 1 2 0 1.5
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