I need help finding nR-Squared

A realty company wants to create a linear model that will estimate the selling price of homes as a function of family. There is particular concern for obtaining the most efficient estimate of the relationship between income and house price. The company has collected data on their sales experience over the past years, and the data are contained in the attached table. Complete parts a though d below. Click the icon to view the data. X Data table Click the icon to view the upper critical values of the chi-square distribution. a. Estimate the regression of house price on family income. Family Income(S) House Price($) House Price = 135205.34 + 1.93 (Family Income) 59,19 248,469 (Round to two decimal places as needed.) 53,377 237,132 53.240 240,44 b. Graphically check for heteroscedasticity. Plot the residuals versus income (X-values). Choose the correct graph below. 52,761 243,981 50,415 243,002 C. O A. O B. 74,314 273,694 he 74,369 276,092 50000- 50000- 60000- 71,975 271,268 8 73,426 271,793 72,08 282,044 39200000 200000 209000 95, 130 332,349 87,564 287,14 500001 500001 500001 95,796 318,255 89,274 314,897 Based on the graph, does it appear that there is heteroscedasticity in the regression errors? 93,490 300,253 108,779 360,320 O A. No, there is no evidence of heteroscedasticity in the regression errors. 110,877 367,439 B. Yes, there is evidence of heteroscedasticity in the regression errors. 119,416 341,694 115,754 363,828 c. Use a formal test of hypothesis to check for heteroscedasticity. Test at the 5% significance level. 115,764 355,934 137,791 359,757 Determine the critical value, Xia 144,247 369,822 147,557 449,339 Xia = 3.841 (Round to three decimal places as needed.) 143,029 452,287 Determine the test statistic for this test for heteroscedasticity. 140,636 399,585 172,207 480,841 (Round to three decimal places as needed.) 173,054 475,614 187,728 532,256 177,069 429,684 171,416 471,242