*must be done in excel
11. Real Estate Data Analysis The Excel file labeled REAL ESTATE contains data on 100 homes sold by a large real estate company in the past three years. You have been asked to provide some analysis of the data for the company's management team Copy the data into a new worksheet in your Excel file to complete the activities described below. Use Excel functions to arrange and analyze the data as required to produce the results described below. Make Excel do all of the work. I must be able to see your functions and formulas in the EXCEL file by foggling to show formulas Report the results in your Excel file close to the analysis that was used. Make sure the work and answers are well labelled and organized so the reader can follow it easily. Use complete sentences to report answers where appropriate. 1. Count of the number of houses that have a garage and the number that do not have a garage Use the Excel COUNTIF function (watch the podcast and if you need additional help with this or any other function use the Excel Help) 2. Create a pie chart to display the results from #1. 3. Count of the number of houses in each of the five locations Use COUNTIF function (watch the podcast and if you need additional help with this or any other function use the Excel Help) 4. Create a bar or column chart to display the results from #3 5. Create the appropriate graph to show the relationship between Price and Size (copy just the Price and Size data into a new worksheet) Regression review and preview ---Think about which variable, Price or Size, is likely to be the dependent variable (the one you want to predict) and which is likely to be the independent variable (the one we use to predict the other). We want the dependent variable to be on the vertical (y) axis and the independent variable to be on the horizontal (x) axis. Excel will automatically put the first column of data on the horizontal axis of a scatterplot and the second column on the vertical axis. Organize your data accordingly to make the graph. 6. Calculate the average size of house sold and the average price (use Excel AVERAGE function). 7. Use the results from 16 to calculate the average price per square foot. 1924 Price = selling price of house in thousands Bedroomse number of bedrooms Size = square feet Pool=binary variable 1 = house has a pool, O = no pool Distance miles to center of city location = what neighborhood the house is located in Mayfair Blueridge Roseland Avondale 5 Wildwood Garage = binary variable 1 = house has a garage, 0 = house has no garage Baths = number of bathrooms 3 House Price Bedrooms Size Pool 1 263.1 4 2300 2 4 2100 3 242.1 3 2300 4 213.6 2 2200 5 149.9 2 2100 2454 2 2100 7 3272 6 2500 8 2718 2 2100 9 225 2 2300 10 266.6 4 2400 11 2924 4 2100 12 208.5 2 1700 13 2708 6 2500 14 2461 4 2100 15 1944 2300 16 2813 3 2100 17 182.7 4 2200 18 2075 5 2300 19 1989 3 2200 20 2093 6 1900 21 2523 4 2800 22 1929 4 1900 23 209.3 5 2100 24 3453 8 2000 25 320.3 6 2100 20 173.1 2 2200 27 1884 2 1900 28 2572 2 2100 90 Distance Location Garage 0 17 2 1 0 19 4 1 0 12 3 O O 16 2 1 D 28 1 D 12 1 1 1 15 3 1 1 9 2 1 O 18 3 0 1 13 1 0 14 3 1 0 1 7 4 1 1 18 1 0 11 3 0 1 16 2 1 D 16 3 0 0 21 4 1 D 10 4 1 0 15 4 1 1 8 4 1 O 14 2 1 1 20 5 0 D 9 4 1 1 11 5 1 O 21 2 1 26 4 O 1 9 1 1 Baths 2 2 2 25 1.5 2 2 25 15 2 2 1.5 2 2 2 2 2 25 2 2 2 25 15 2 3 15 2 2 16 2 - 14 27 28 2 2 3 26 9 14 0 1 1 1 D 0 1 1 1900 2100 2200 2000 1700 2000 2400 2000 1900 30 31 32 33 34 35 11 19 2 2 2 5 3 4 1 3 5 3 5 2 2 5 4 2 5 0 1 1 1 11 16 16 10 2 2 15 2 2 2 2 2 2 25 2 25 2 2 4 1 1 1 0 1 37 38 39 40 41 42 4 6 3 5 1884 2572 235.5 1804 236.5 208.5 2477 1662 177.1 182.7 217.9 312.1 199.8 2732 216.9 2322 1983 205.1 175.0 3078 2692 2248 171.6 216.8 1926 2304 1724 2514 1894 312.1 19 7 19 16 9 1 1 0 1 0 1 1 1 1 0 0 0 0 0 D 0 1 D 3 3 4 3 2 3 2 1 4 2300 2800 2100 2200 2100 1900 2100 2000 2300 2400 2200 2200 2000 2200 2200 2200 2200 1900 2200 2400 1 0 1 1 0 1 1 1 4 44 45 46 47 5 15 1.5 1.5 2 2 3 3 25 2 2 2 2 16 19 20 24 21 8 17 16 15 14 20 23 12 4 2 5 1 4 49 1 0 1 3 3 3 6 5 3 3 4 1 1 3 3 $1 52 53 54 55 56 D 1 1 O 1 0 1 0 1 1 2 2 2 1 2 13 7 13 6 1 1 1 0 56 57 58 59 60 61 62 63 1 1 0 1 1 3 3 25 5 2 2 5 3 2400 2000 2200 2000 2100 2200 2200 2500 2100 2200 2100 2000 2400 1900 21 11 13 9 13 18 15 2 2 2 1 1 4 0 0 D D 0 1 3 4 10 19 13 0 1 1 0 17 8 6 1 1 1900 0 312.1 289.8 269.9 1543 222.1 209.7 190.9 2543 207.5 209.7 295 2 176.3 294.3 2262 1263 236.8 164.1 2178 1922 125.9 220.9 294,5 244,6 2011 2413 263 2 1881 243.7 221,5 1762 D 1 0 1 D 1 1 D 3 3 4 2 5 2 3 3 2 2 2 3 4 1 4 5 4 3 2 1 2 3 2 1 4 3 4 2 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 80 84 85 2 2 7 3 2 4 4 3 2 2 2 6 2 3 4 1 0 1 2600 2300 2500 2400 2400 2300 2700 2300 2500 2000 2300 1900 2700 2300 2500 2 2 2 2 25 2 2 2 1.5 2 2 2 25 1.5 2 2 2.5 15 2 2 15 2 18 17 19 12 16 28 12 15 9 18 13 0 0 1 1 D 1 1 1 1 1 1 1 0 1 1 1 1 4 2 6 4 1 1 1 8 7 10 D 73 74 75 76 77 1 D 0 0 1 1 1 3 2 1 2 3 2 1 1 1 1 1 1 2 25 1.5 2 2 25 1.5 2 2 15 2 0 79 80 81 0 1 1 1 1 3 4 1 1 D 3 2 2 2 5 2 3 4 4 2 6 4 2 3 4 5 3 6 4 4 5 8 6 2 3 2178 1922 125.9 220,9 294.5 244,6 2011 2413 263 2 188.1 243.7 221.5 176.2 253.2 1554 186.7 1801 1883 2271 173.6 188.3 311.8 2945 1812 1883 2271 183.6 1883 2 12 16 28 12 15 9 18 13 14 8 7 18 11 16 16 21 10 15 8 14 20 9 11 2500 2400 2400 2300 2700 2300 2500 2800 2300 1900 2700 2300 2500 2300 2400 2500 2400 2100 2900 2100 2300 2000 2400 2400 2100 2000 2100 2300 83 84 85 86 87 88 89 90 91 92 90 94 95 05 97 9 1 1 1 0 1 0 1 2 3 4 0 0 D 0 O 1 0 2 1 1 1 4 2 5 4 1 2 2 2 25 2 2 2 2.5 1.5 2 3 2 25 15 2 3 1 0 1 1 1 1 3 1 1 1 D 0 1 1 6 14 20 9 5 4 2 5 4 5 4 0 1 1 100 House 1 NMN Baths 1 1 0 1 1 1 1 0 1 1 NNNNNNNNNNNNNNNNN 1 1 1 0 1 0 1 1 1 1 1 0 1 1 2.5 1 Price Bedrooms Size 263.1 Pool 2 4 192.4 2300 3 4 2100 242.1 4 3 2300 213.6 2 5 2200 149.9 2 6 2100 245.4 2100 7 3272 6 2500 8 271.8 2 2100 9 225.2 3 2300 10 266.6 4 2400 11 292.4 4 2100 12 208.5 2 1700 13 270.8 6 2500 14 246.1 4 2100 15 194.4 2 2300 16 281.3 3 2100 17 182.7 4 2200 18 207.5 5 2300 19 198.9 3 2200 20 209.3 6 1900 21 252.3 4 2600 22 192.9 4 1900 23 209.3 5 2100 24 345.3 8 2600 25 326.3 6 2100 26 173.1 2 2200 27 188.4 2 1900 28 257.2 2 2100 29 235.5 3 2200 30 180.4 2 2000 31 236.5 2 1700 32 208.5 2 2000 33 247.7 5 2400 34 166.2 3 2000 35 177.1 2 1900 36 182.7 4 2000 37 217.9 4 2300 38 312.1 6 2600 39 199.8 3 2100 40 273.2 5 2200 41 216.9 3 2100 42 232.2 3 1900 43 198.3 4 2100 44 205.1 3 2000 4 175.6 45 2300 46 2400 3 307.8 47 269.2 2200 48 224.8 3 2200 49 171.6 3 2000 50 216.8 3 2200 51 192.6 2200 Distance Location Garage 0 17 0 19 0 12 0 16 0 28 1 0 12 1 15 3 2 0 18 3 1 13 4 0 14 0 8 4 1 7 4 1 18 3 0 11 3 1 16 2 16 3 0 21 0 10 0 15 4 1 8 4 0 14 1 20 5 0 9 4 1 11 5 0 21 2 26 4 1 9 1 0 14 3 11 5 1 19 3 1 11 5 16 2 0 16 2 1 10 5 0 14 1 19 2 7 5 19 3 1 16 2 0 9 3 16 2 19 1 20 4 24 4 21 2 8 5 17 1 16 4 15 14 1 0 1 1 0 1 0 NONNNNNNNNNNN 1 1 0 1 1 1 1 1 0 1 1 0 ANAANWNW ONUN OOOOOOOO 3 1.5 1.5 1.5 2 2 3 3 2.5 1 1 1 -OO 2200 3 1 0 1 1 1 0 1 WNNN WWN ON WW NW W 5 3 3 4 7 6 5 2 2 5 3 4 3 4 2 2 7 3 2 4 4 3 2 2 1 1 1 0 1 1 1 0 1 1 0 0 0 0 0 1 0 1 0 1 0 1 1 0 0 0 NNNNNNNNNNNNN 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 1 0 1 0 1 1 0 1 0 1 1 236.4 172.4 251.4 189.4 312.1 289.8 269.9 154.3 222.1 209.7 190.9 254.3 207.5 209.7 295.2 176.3 294.3 226.2 126.3 236.8 164.1 217.8 192.2 125.9 220.9 294.5 244.6 201.1 241.3 263.2 188.1 243.7 221.5 176.2 253.2 155.4 186.7 180.1 188.3 227.1 173.6 188.3 311.8 294.5 181.2 188.3 227.1 183.6 188.3 20 23 12 24 13 21 11 13 9 13 18 15 10 19 13 17 8 6 18 17 19 12 16 28 12 15 9 18 13 14 8 7 18 11 16 16 21 10 15 8 14 20 9 11 8 14 20 9 11 2200 1900 2200 2400 2000 2200 2000 2100 2200 2200 2500 2100 2200 2100 2000 2400 1900 1900 2600 2300 2500 2400 2400 2300 2700 2300 2500 2600 2300 1900 2700 2300 2500 2300 2400 2500 2400 2100 2900 2100 2300 2900 2400 2400 2100 2900 2100 2300 1 2 3 3 2 2 2 3 4 1 4 5 4 3 2 1 2 3 2 1 4 3 4 2 3 3 2 3 4 4 2 4 2 5 4 5 4 2 5 4 5 1 1 1 1 0 1 1 1 1 1 0 1 0 1 1 1 1 1 0 0 0 0 0 0 1 0 1 85 2 1.5 2 2 2 2.5 1.5 2 2 2.5 1.5 2 2 1.5 2 2 2 2 2 2.5 2 2 2 2.5 1.5 2 3 2 2.5 1.5 2 1 0 1 1 6 4 2 3 4 5 3 6 4 4 5 8 6 3 6 4 4 5 1 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 1 0 1 1 1 1 1 0 0 1 0 1 1 1 Price = selling price of house in $thousands Bedrooms = number of bedrooms Size = square feet Pool = binary variable 1 = house has a pool, 0 = no pool Distance = miles to center of city location = what neighborhood the house is located in 1 = Mayfair 2= Blueridge 3= Roseland 4 = Avondale 5 = Wildwood Garage = binary variable 1 = house has a garage, 0 = house has no garage Baths = number of bathrooms 11. Real Estate Data Analysis The Excel file labeled REAL ESTATE contains data on 100 homes sold by a large real estate company in the past three years. You have been asked to provide some analysis of the data for the company's management team Copy the data into a new worksheet in your Excel file to complete the activities described below. Use Excel functions to arrange and analyze the data as required to produce the results described below. Make Excel do all of the work. I must be able to see your functions and formulas in the EXCEL file by foggling to show formulas Report the results in your Excel file close to the analysis that was used. Make sure the work and answers are well labelled and organized so the reader can follow it easily. Use complete sentences to report answers where appropriate. 1. Count of the number of houses that have a garage and the number that do not have a garage Use the Excel COUNTIF function (watch the podcast and if you need additional help with this or any other function use the Excel Help) 2. Create a pie chart to display the results from #1. 3. Count of the number of houses in each of the five locations Use COUNTIF function (watch the podcast and if you need additional help with this or any other function use the Excel Help) 4. Create a bar or column chart to display the results from #3 5. Create the appropriate graph to show the relationship between Price and Size (copy just the Price and Size data into a new worksheet) Regression review and preview ---Think about which variable, Price or Size, is likely to be the dependent variable (the one you want to predict) and which is likely to be the independent variable (the one we use to predict the other). We want the dependent variable to be on the vertical (y) axis and the independent variable to be on the horizontal (x) axis. Excel will automatically put the first column of data on the horizontal axis of a scatterplot and the second column on the vertical axis. Organize your data accordingly to make the graph. 6. Calculate the average size of house sold and the average price (use Excel AVERAGE function). 7. Use the results from 16 to calculate the average price per square foot. 1924 Price = selling price of house in thousands Bedroomse number of bedrooms Size = square feet Pool=binary variable 1 = house has a pool, O = no pool Distance miles to center of city location = what neighborhood the house is located in Mayfair Blueridge Roseland Avondale 5 Wildwood Garage = binary variable 1 = house has a garage, 0 = house has no garage Baths = number of bathrooms 3 House Price Bedrooms Size Pool 1 263.1 4 2300 2 4 2100 3 242.1 3 2300 4 213.6 2 2200 5 149.9 2 2100 2454 2 2100 7 3272 6 2500 8 2718 2 2100 9 225 2 2300 10 266.6 4 2400 11 2924 4 2100 12 208.5 2 1700 13 2708 6 2500 14 2461 4 2100 15 1944 2300 16 2813 3 2100 17 182.7 4 2200 18 2075 5 2300 19 1989 3 2200 20 2093 6 1900 21 2523 4 2800 22 1929 4 1900 23 209.3 5 2100 24 3453 8 2000 25 320.3 6 2100 20 173.1 2 2200 27 1884 2 1900 28 2572 2 2100 90 Distance Location Garage 0 17 2 1 0 19 4 1 0 12 3 O O 16 2 1 D 28 1 D 12 1 1 1 15 3 1 1 9 2 1 O 18 3 0 1 13 1 0 14 3 1 0 1 7 4 1 1 18 1 0 11 3 0 1 16 2 1 D 16 3 0 0 21 4 1 D 10 4 1 0 15 4 1 1 8 4 1 O 14 2 1 1 20 5 0 D 9 4 1 1 11 5 1 O 21 2 1 26 4 O 1 9 1 1 Baths 2 2 2 25 1.5 2 2 25 15 2 2 1.5 2 2 2 2 2 25 2 2 2 25 15 2 3 15 2 2 16 2 - 14 27 28 2 2 3 26 9 14 0 1 1 1 D 0 1 1 1900 2100 2200 2000 1700 2000 2400 2000 1900 30 31 32 33 34 35 11 19 2 2 2 5 3 4 1 3 5 3 5 2 2 5 4 2 5 0 1 1 1 11 16 16 10 2 2 15 2 2 2 2 2 2 25 2 25 2 2 4 1 1 1 0 1 37 38 39 40 41 42 4 6 3 5 1884 2572 235.5 1804 236.5 208.5 2477 1662 177.1 182.7 217.9 312.1 199.8 2732 216.9 2322 1983 205.1 175.0 3078 2692 2248 171.6 216.8 1926 2304 1724 2514 1894 312.1 19 7 19 16 9 1 1 0 1 0 1 1 1 1 0 0 0 0 0 D 0 1 D 3 3 4 3 2 3 2 1 4 2300 2800 2100 2200 2100 1900 2100 2000 2300 2400 2200 2200 2000 2200 2200 2200 2200 1900 2200 2400 1 0 1 1 0 1 1 1 4 44 45 46 47 5 15 1.5 1.5 2 2 3 3 25 2 2 2 2 16 19 20 24 21 8 17 16 15 14 20 23 12 4 2 5 1 4 49 1 0 1 3 3 3 6 5 3 3 4 1 1 3 3 $1 52 53 54 55 56 D 1 1 O 1 0 1 0 1 1 2 2 2 1 2 13 7 13 6 1 1 1 0 56 57 58 59 60 61 62 63 1 1 0 1 1 3 3 25 5 2 2 5 3 2400 2000 2200 2000 2100 2200 2200 2500 2100 2200 2100 2000 2400 1900 21 11 13 9 13 18 15 2 2 2 1 1 4 0 0 D D 0 1 3 4 10 19 13 0 1 1 0 17 8 6 1 1 1900 0 312.1 289.8 269.9 1543 222.1 209.7 190.9 2543 207.5 209.7 295 2 176.3 294.3 2262 1263 236.8 164.1 2178 1922 125.9 220.9 294,5 244,6 2011 2413 263 2 1881 243.7 221,5 1762 D 1 0 1 D 1 1 D 3 3 4 2 5 2 3 3 2 2 2 3 4 1 4 5 4 3 2 1 2 3 2 1 4 3 4 2 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 80 84 85 2 2 7 3 2 4 4 3 2 2 2 6 2 3 4 1 0 1 2600 2300 2500 2400 2400 2300 2700 2300 2500 2000 2300 1900 2700 2300 2500 2 2 2 2 25 2 2 2 1.5 2 2 2 25 1.5 2 2 2.5 15 2 2 15 2 18 17 19 12 16 28 12 15 9 18 13 0 0 1 1 D 1 1 1 1 1 1 1 0 1 1 1 1 4 2 6 4 1 1 1 8 7 10 D 73 74 75 76 77 1 D 0 0 1 1 1 3 2 1 2 3 2 1 1 1 1 1 1 2 25 1.5 2 2 25 1.5 2 2 15 2 0 79 80 81 0 1 1 1 1 3 4 1 1 D 3 2 2 2 5 2 3 4 4 2 6 4 2 3 4 5 3 6 4 4 5 8 6 2 3 2178 1922 125.9 220,9 294.5 244,6 2011 2413 263 2 188.1 243.7 221.5 176.2 253.2 1554 186.7 1801 1883 2271 173.6 188.3 311.8 2945 1812 1883 2271 183.6 1883 2 12 16 28 12 15 9 18 13 14 8 7 18 11 16 16 21 10 15 8 14 20 9 11 2500 2400 2400 2300 2700 2300 2500 2800 2300 1900 2700 2300 2500 2300 2400 2500 2400 2100 2900 2100 2300 2000 2400 2400 2100 2000 2100 2300 83 84 85 86 87 88 89 90 91 92 90 94 95 05 97 9 1 1 1 0 1 0 1 2 3 4 0 0 D 0 O 1 0 2 1 1 1 4 2 5 4 1 2 2 2 25 2 2 2 2.5 1.5 2 3 2 25 15 2 3 1 0 1 1 1 1 3 1 1 1 D 0 1 1 6 14 20 9 5 4 2 5 4 5 4 0 1 1 100 House 1 NMN Baths 1 1 0 1 1 1 1 0 1 1 NNNNNNNNNNNNNNNNN 1 1 1 0 1 0 1 1 1 1 1 0 1 1 2.5 1 Price Bedrooms Size 263.1 Pool 2 4 192.4 2300 3 4 2100 242.1 4 3 2300 213.6 2 5 2200 149.9 2 6 2100 245.4 2100 7 3272 6 2500 8 271.8 2 2100 9 225.2 3 2300 10 266.6 4 2400 11 292.4 4 2100 12 208.5 2 1700 13 270.8 6 2500 14 246.1 4 2100 15 194.4 2 2300 16 281.3 3 2100 17 182.7 4 2200 18 207.5 5 2300 19 198.9 3 2200 20 209.3 6 1900 21 252.3 4 2600 22 192.9 4 1900 23 209.3 5 2100 24 345.3 8 2600 25 326.3 6 2100 26 173.1 2 2200 27 188.4 2 1900 28 257.2 2 2100 29 235.5 3 2200 30 180.4 2 2000 31 236.5 2 1700 32 208.5 2 2000 33 247.7 5 2400 34 166.2 3 2000 35 177.1 2 1900 36 182.7 4 2000 37 217.9 4 2300 38 312.1 6 2600 39 199.8 3 2100 40 273.2 5 2200 41 216.9 3 2100 42 232.2 3 1900 43 198.3 4 2100 44 205.1 3 2000 4 175.6 45 2300 46 2400 3 307.8 47 269.2 2200 48 224.8 3 2200 49 171.6 3 2000 50 216.8 3 2200 51 192.6 2200 Distance Location Garage 0 17 0 19 0 12 0 16 0 28 1 0 12 1 15 3 2 0 18 3 1 13 4 0 14 0 8 4 1 7 4 1 18 3 0 11 3 1 16 2 16 3 0 21 0 10 0 15 4 1 8 4 0 14 1 20 5 0 9 4 1 11 5 0 21 2 26 4 1 9 1 0 14 3 11 5 1 19 3 1 11 5 16 2 0 16 2 1 10 5 0 14 1 19 2 7 5 19 3 1 16 2 0 9 3 16 2 19 1 20 4 24 4 21 2 8 5 17 1 16 4 15 14 1 0 1 1 0 1 0 NONNNNNNNNNNN 1 1 0 1 1 1 1 1 0 1 1 0 ANAANWNW ONUN OOOOOOOO 3 1.5 1.5 1.5 2 2 3 3 2.5 1 1 1 -OO 2200 3 1 0 1 1 1 0 1 WNNN WWN ON WW NW W 5 3 3 4 7 6 5 2 2 5 3 4 3 4 2 2 7 3 2 4 4 3 2 2 1 1 1 0 1 1 1 0 1 1 0 0 0 0 0 1 0 1 0 1 0 1 1 0 0 0 NNNNNNNNNNNNN 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 1 0 1 0 1 1 0 1 0 1 1 236.4 172.4 251.4 189.4 312.1 289.8 269.9 154.3 222.1 209.7 190.9 254.3 207.5 209.7 295.2 176.3 294.3 226.2 126.3 236.8 164.1 217.8 192.2 125.9 220.9 294.5 244.6 201.1 241.3 263.2 188.1 243.7 221.5 176.2 253.2 155.4 186.7 180.1 188.3 227.1 173.6 188.3 311.8 294.5 181.2 188.3 227.1 183.6 188.3 20 23 12 24 13 21 11 13 9 13 18 15 10 19 13 17 8 6 18 17 19 12 16 28 12 15 9 18 13 14 8 7 18 11 16 16 21 10 15 8 14 20 9 11 8 14 20 9 11 2200 1900 2200 2400 2000 2200 2000 2100 2200 2200 2500 2100 2200 2100 2000 2400 1900 1900 2600 2300 2500 2400 2400 2300 2700 2300 2500 2600 2300 1900 2700 2300 2500 2300 2400 2500 2400 2100 2900 2100 2300 2900 2400 2400 2100 2900 2100 2300 1 2 3 3 2 2 2 3 4 1 4 5 4 3 2 1 2 3 2 1 4 3 4 2 3 3 2 3 4 4 2 4 2 5 4 5 4 2 5 4 5 1 1 1 1 0 1 1 1 1 1 0 1 0 1 1 1 1 1 0 0 0 0 0 0 1 0 1 85 2 1.5 2 2 2 2.5 1.5 2 2 2.5 1.5 2 2 1.5 2 2 2 2 2 2.5 2 2 2 2.5 1.5 2 3 2 2.5 1.5 2 1 0 1 1 6 4 2 3 4 5 3 6 4 4 5 8 6 3 6 4 4 5 1 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 1 0 1 1 1 1 1 0 0 1 0 1 1 1 Price = selling price of house in $thousands Bedrooms = number of bedrooms Size = square feet Pool = binary variable 1 = house has a pool, 0 = no pool Distance = miles to center of city location = what neighborhood the house is located in 1 = Mayfair 2= Blueridge 3= Roseland 4 = Avondale 5 = Wildwood Garage = binary variable 1 = house has a garage, 0 = house has no garage Baths = number of bathrooms
