# Assignment 2

.xlsx
Student GPA Experience Salary 1 2.92 3 73,590 2 3.84 9 87,000 If the multiple regression equatio 3 3.04 6 76,970 4 3.20 6 79,320 Explain: Remove the p-value with result high 5 3.61 7 79,530 Remove the variable from the model and ev 6 2.99 5 71,040 Delete the variables not significicantly affect 7 3.78 8 82,050 8 3.20 5 78,890 9 3.42 7 82,170 10 3.05 5 76,120 SUMMARY OUTPUT 11 3.12 4 77,500 12 3.56 7 83,920 Regression Statistics 13 3.01 5 71,800 Multiple R 0.838484 14 3.15 6 77,000 R Square 0.703056 15 3.05 7 79,000 Adjusted R 0.687005 16 3.24 5 77,800 Standard E 2220.671 17 3.25 6 80,600 Observatio 40 18 3.78 9 87,000 19 3.12 4 78,450 ANOVA 20 3.24 8 80,600 df SS MS 21 2.98 5 74,900 Regression 2 4.32E+08 2.16E+08 22 3.24 6 79,200 Residual 37 1.82E+08 4931380 23 3.08 4 77,000 Total 39 6.14E+08 24 3.00 6 77,900 25 2.95 4 76,950 Coefficients tandard Erro t Stat 26 3.01 5 76,800 Intercept 53295.45 4566.511 11.67093 27 3.23 7 79,300 GPA 5539.797 1696.536 3.265358 28 3.01 2 72,120 Experience 1257.259 282.8412 4.445103 29 3.45 7 83,900 30 3.85 8 85,200 31 3.00 5 77,300 At this point, Significant F is smaller than 0, w 32 3.23 6 83,500 when we remove unnecessary variable is sc 33 3.80 7 77,000 This is tell us that all of variables are significa 34 3.08 5 75,000 35 3.15 7 79,200 Improve multiple regression equa 36 3.35 7 80,400 y = (1257.259*Experience) +(553 37 3.09 7 80,200 for example: student 36 with GPA 38 3.35 9 84,800 y = (1257.259 * 7) + (5539.797* 3 39 3.16 3 72,800 40 2.76 7 75,000
on in the previous question is not "good for use", how would you suggest impr her than 0.05 because not contribute in significance in explaining the data given, which is school ranking d valuate adjusted R squareto see how much impact in new model to the data F ignificance F 43.8013075182 1.756E-10 P-value Lower 95%Upper 95%Lower 99.0% Upper 99.0% 5.7837517E-14 44042.82 62548.08 40895.5 65695.39 0.00235962571 2102.289 8977.304 933.009 10146.58 7.7134804E-05 684.1677 1830.349 489.229 2025.288 which is good. R square is 70.30%, and adjusted r square is smaller than r square is 68.7% which are als chool ranking, all of the p-value of GPA and Experience are very small and close to 0, smaller than 0.05. ant, good fit data. ation and numeric example 39.797 *GPA) +53295.45 A is 3.35 and experience is 7 3.35) + 53295.45 = 80654.58
roving this multiple regression equation? Present the improved multiple regression due to the p-value higher than 0.05 for question 4 answer so good fit.