Calculate and interpret the coefficient of correlation for squarefeet and price2

Question

Calculate and interpret the coefficient of correlation for squarefeet and price2014.

housenum price2014 distance garage_spaces no_rooms squarefeet Zip (1062 = 1) no_full_baths no_half_baths bedrooms acre zip 1 210.729 2.4 2 5 0.966 1 1 0 3 0.28 1062 2 204.171 1.97 1 5 0.96 1 1 0 3 0.29 1062 3 338.662 0.043371212 2 7 1.725 1 2 1 3 0.36 1062 4 276.25 0.554734848 1 6 1.727 0 1 1 3 0.26 1060 5 169.173 0.596590909 0 6 1.576 1 1 0 4 0.31 1062 6 211.487 1.88 1 6 1.32 1 1 1 3 0.31 1062 7 311.456 0.444886364 0 6 1.202 0 1 0 3 0.08 1060 8 377.857 0.444886364 0 9 2.136 0 1 1 4 0.11 1060 9 227.681 1.93 0 7 1.918 1 2 0 5 0.31 1062 10 224.366 2.873030303 0 5 1.008 1 1 0 3 0.27 1062 11 218.785 0.756628788 0 5 1.296 1 2 0 3 0.27 1062 12 269.62 1.41 2 7 1.432 1 1 0 3 0.51 1062 13 447.842 1.42155303 0 8 2.04 0 2 0 4 0.23 1060 14 386.446 0.246780303 0 6 1.604 0 1 1 3 0.11 1060 15 528.114 0.396022727 0 9 2.278 0 2 0 4 0.15 1060 16 221.22 1.567234848 0 6 1.208 1 1 0 3 0.23 1062 17 320.206 1.676704545 0 7 1.744 1 2 0 5 0.23 1062 18 179.487 1.598674242 0 5 1.008 1 1 0 3 0.23 1062 19 243.639 0.103030303 0 8 1.922 0 1 1 4 0.31 1060 20 325.666 0.3375 0 8 2.1 0 2 0 4 0.07 1060 21 282.765 1 1 7 1.664 1 2 0 4 0.23 1062 22 198.686 0.042045455 1 5 0.892 1 1 0 2 0.17 1062 23 168.761 2.15 0 5 1.01 1 1 0 3 0.33 1062 24 200.871 2.621401515 0 6 1.248 1 1 1 3 0.33 1062 25 237.206 2.579734848 1 6 1.3 1 2 0 3 0.31 1062 26 205.77 2.7 1 5 1.04 1 1 0 3 0.34 1062 27 287.489 0.216738636 0 8 1.466 0 1 0 4 0.13 1060 28 223.067 1.91 1 6 1.636 1 1 0 3 0.23 1062 29 237.594 0.708522727 1 7 1.335 1 1 0 4 0.21 1062 30 275.218 2.011742424 0 6 1.512 1 2 0 4 0.14 1062 31 280.283 1.991666667 1 8 1.752 1 2 0 4 0.21 1062 32 237.789 0.892045455 0 8 1.912 0 1 0 3 0.14 1060 33 191.694 0.875378788 0 5 0.942 1 1 0 3 0.26 1062 34 365.506 0.329545455 0 8 1.675 0 2 0 3 0.56 1060 35 474.245 0.326515152 1 7 1.8 0 2 0 4 0.11 1060 36 259.48 0.704356061 0 6 1.412 1 2 0 3 0.32 1062 37 326.891 0.866856061 2 7 1.763 1 2 0 3 0.5 1062 38 228.829 0.204734848 2 7 1.796 0 2 0 4 0.34 1060 39 426.5 0.138825758 2 7 2.224 0 2 0 4 0.19 1060 40 350.766 1.145454545 0 6 1.602 0 1 0 3 0.11 1060 41 279.187 0.179545455 1 9 1.9 1 2 0 4 0.28 1062 42 214.737 2.28 0 6 1.348 0 1 0 3 0.1 1060 43 212.959 2.28 0 5 1.084 0 1 0 2 0.1 1060 44 301.366 0.421969697 0 4 1.83 0 1 1 2 0.1 1060 45 144.366 2.28 0 4 0.587 0 1 0 2 0.1 1060 46 318.348 2.28 0 6 1.389 0 2 0 3 0.1 1060 47 185.141 2.28 0 4 0.645 0 1 0 1 0.1 1060 48 132.135 2.28 0 4 0.804 0 1 0 1 0.1 1060 49 200.219 2.28 0 5 0.8 0 1 0 2 0.1 1060 50 525.112 1.21 2 8 3.07 1 3 0 5 0.26 1062 51 210.701 2.53 2 5 0.864 1 1 1 3 0.35 1062 52 185.508 3.48 0 5 0.864 1 1 0 3 0.46 1062 53 209.945 2.4 0 6 1.008 1 1 0 4 0.43 1062 54 142.702 0.126893939 0 4 0.524 0 1 0 1 0.28 1060 55 367.384 0.73219697 0 7 1.856 1 1 1 2 0.55 1062 56 201.443 0.935037879 0 5 0.96 1 1 0 3 0.28 1062 57 360.87 0.390530303 2 9 2.542 1 1 1 4 0.55 1062 58 313.64 0.285795455 1 8 1.395 1 1 0 3 0.18 1062 59 270.622 0.203598485 1 7 1.349 1 2 0 3 0.26 1062 60 258.091 0.502462121 0 6 1.3 1 1 1 2 0.25 1062 61 357.303 0.096780303 2 8 2.256 1 1 1 4 0.22 1062 62 289.946 0.115340909 2 5 1.519 1 1 0 2 0.31 1062 63 296.142 0.385984848 2 7 1.454 1 1 0 3 0.26 1062 64 331.387 0.75625 1 6 1.584 1 1 1 3 0.19 1062 65 389.242 0.6375 2 7 1.624 0 1 0 4 0.14 1060 66 495.218 0.111363636 2 11 2.85 0 3 0 6 0.24 1060 67 246.02 0.300568182 1 7 1.376 1 1 0 3 0.37 1062 68 212.892 1.58 1 7 1.427 1 1 0 3 0.28 1062 69 384.14 0.166098485 1 8 1.837 0 1 1 3 0.23 1060 70 295.182 0.192045455 0 7 1.386 0 1 0 3 0.16 1060 71 520.147 0.35530303 2 6 1.966 0 2 1 3 0.2 1060 72 284.484 0.165719697 0 6 1.376 0 1 0 3 0.12 1060 73 228.565 1.72 0 6 1.2 0 2 0 3 0.33 1060 74 447.27 0.911363636 2 8 1.734 1 2 0 3 0.33 1062 75 286.163 0.785227273 0 7 1.556 1 2 0 3 0.36 1062 76 222.864 0.985984848 0 6 1.7 1 2 0 3 0.38 1062 77 310.018 0.35719697 1 7 2.042 0 2 0 4 0.18 1060 78 211.725 1.871780303 1 6 1.32 1 1 1 3 0.39 1062 79 266.124 2.89 2 7 1.728 1 1 0 3 0.46 1062 80 214.289 2.94280303 1 6 1.294 1 1 0 3 0.27 1062 81 211.104 1.589962121 1 5 0.966 1 1 0 3 0.51 1062 82 216.992 1.939962121 0 4 1.008 1 1 0 2 0.54 1062 83 202.485 2.577083333 2 7 1.594 1 1 1 3 0.35 1062 84 429.368 0.200189394 1 9 1.817 1 1 1 4 0.22 1062 85 208.703 1.75 0 5 0.96 1 1 0 3 0.28 1062 86 249.413 0.154356061 1 7 1.344 0 1 0 4 0.18 1060 87 332.674 0.385984848 2 7 1.5 1 2 0 4 0.17 1062 88 356.265 0.381818182 2 8 2.448 0 1 0 5 0.15 1060 89 513.096 0.624431818 2 14 4.03 0 3 1 5 0.35 1060 90 236.498 1.891060606 1 7 1.638 1 2 0 4 0.25 1062 91 295.772 1.887272727 1 7 1.772 1 2 0 4 0.43 1062 92 421.46 0.416477273 4 5 2.137 0 2 0 2 0.09 1060 93 233.023 0.038825758 0 4 0.934 0 2 0 2 0.05 1060 94 279.814 0.144507576 2 5 1.457 1 1 1 3 0.22 1062 95 347.408 0.153219697 1 7 1.737 1 4 0 4 0.25 1062 96 267.29 0.258712121 1 6 1.262 0 1 0 3 0.12 1060 97 879.328 0.458143939 1 12 3.175 0 3 0 6 0.26 1060 98 191.407 3.976780303 0 6 1.041 1 2 0 2 0.23 1062 99 467.861 0.674810606 0 9 2.102 0 2 1 3 0.19 1060 100 301.94 0.950568182 0 8 1.859 0 2 0 3 0.13 1060 101 534.865 0.764204545 2 9 2.528 0 2 1 4 0.46 1060 102 331.84 0.125189394 0 8 1.96 1 2 0 4 0.4 1062 103 320.805 1.070265152 0 8 1.941 0 1 0 4 0.2 1060 104 176.502 0.723295455 0 5 1.197 1 1 0 2 0.31 1062

Explanation / Answer

The correlation coefficient between the two variables such as Price2014 and square feet is given as 0.801669, this means, there is a high positive or strong positive linear association or linear relationship or correlation exists between the two variables Price 2014 and square feet.

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