Use KSTAT to perform a regression of price vs income . write out the estimated r

Question

Use KSTAT to perform a regression of price vs income . write out the estimated regression equation .....PLEASE SHOW WHAT WAS INPUTED IN THE REGRESSION DATA ANALYSIS TOOL TO GET THE ANSWER.

Income Price 72100 21800 55200 23000 58500 12400 50700 23400 58300 24700 23000 5100 58700 19200 38400 12600 63600 19400 69500 16900 83300 30600 50400 20600 48200 20100 63400 23300 57000 21100 57400 16200 87800 19900 61600 19900 58500 21700 92100 23800 50200 8700 82600 21000 60700 13200 59900 26800 88300 21900 67100 27100 68400 22300 57000 27700 72600 18600 59800 19600 48400 13100 42300 22100 64400 19400 44300 15200 93900 27100 58800 14400 34000 15300 55200 27400 77200 25800 54400 12800 49800 11700 37700 15600 66300 22400 58200 16600 70700 25200 50100 13300 55100 18600 65800 23000 55300 20600 64600 19600 18900 13900 59800 20300 65100 27100 96900 26600 35000 8100 34500 11700 21800 15700 80900 25100 101300 32500 54300 15300 43900 10300 70300 20400 72200 15500 46500 24000 74700 20500 72200 28300 57400 11800 34600 13900 78200 21000 73900 26600 55000 27300 49200 13000 75600 24600 66800 29700 70400 19700 96400 31300 65600 17800 42100 14600 69100 17000 40100 15200 70600 17300 58300 17700 66000 22900 67000 23600 63200 17200 56300 18400 38000 12500 97000 22100 88100 25400 78800 29600 35800 14100 42000 14700 70000 26500 62200 18300 60800 13300 63700 24400 29000 12900 56600 14600 45000 15200 44000 10900

Explanation / Answer

The regression equation is

y=a+bx

from Excel

The fitted equation is

y=5787.9 +0.2274(Income)

SUMMARY OUTPUT Regression Statistics Multiple R 0.675778067 R Square 0.456675995 Adjusted R Square 0.451131873 Standard Error 4266.857806 Observations 100 ANOVA df SS MS F Significance F Regression 1 1.5E+09 1.5E+09 82.37119 1.23E-14 Residual 98 1.78E+09 18206076 Total 99 3.28E+09 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 5787.899881 1572.261 3.681258 0.00038 2667.798 8908.001 2667.798 8908.001 Income 0.22754022 0.025071 9.075858 1.23E-14 0.177788 0.277293 0.177788 0.277293

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