Interpret the adjusted R-square result. What does it tell us? Interpret the coef

Question

Interpret the adjusted R-square result. What does it tell us?

Interpret the coefficients for statistically significant variables. Be precise. Do not use the word “units”.

T X Review Filter commands here Command rc Alavi mport excel set more off gen female- 1 if gender replace female 0 if gender. st gender female Tabulate region, gen(locati 7 tabulate region, gen(locati rename location1 midwest 9 rename location2 northeast 10 rename location3 south 11 rename location4 west 12 regress wage monthly lQy northeast 72 7.70 31.87 uth 335 35.83 67.70 302 32.30 100.00 eSt. Total 935 100.00 rename location1 midwest. rename location2 northeast rename location3 south. rename location4 west. regress wage monthly IQ yrs educ age mom educ female northeast south west So 857 urCe F (8 848) 55.41 8 6091851.7 Prob F Model 48734813.6 0.0000 93230942.5 esidual 848 109942.149 squared 0.3433 Ad j R squared 0.3371 856 165847.846 Root MSE Total 141965756 331.58 wage monthly Coef Std Err P It 95% Conf Interval] 928191 3.244609 3.50 0.000 1.422788 5.06643 27.84085 6.260833 40.12939 yrs educ 4.45 0.000 15.5523 5.484 623 3.896231 809262 4.81 0.000 2.30784 age educ 3.9085 4.380233 0.89 0.372 4.688871 12.50587 mom. 91.36244 31.17207 female 2.93 0.003 152.5459 30.17897 6.090755 47.30527 0.13 0.898 86.75839 98.9399 northea8t 168 1914 30.46098 south 5.52 0.000 227.9792 108.4036 166.5855 287.1248 226.8551 30.7065 7.39 0.000 eSt. 364.376 100.4245 3.63 0.000 167.2662 561.4858 Con

Explanation / Answer

Here the value of adjusted R-square is 0.3371; this value says how well terms fit a curve or line after adjusting the number of terms in a model. In regression model if we add more and more useless variables to a model then adjusted r-squared will decrease. On the other hand if we add more useful variables, adjusted r-squared will increase. Here the R-square is 0.3433 which is more than the adjusted R-square and it is always true that Adjusted R-square will be always less than or equal to R-square.

If the p-value is less than .05 (level of significance) then we can conclude that the coefficient is statistically significant. We find that for the following variables the t-test p-value is less than the level of significance; they are statistically significant.

yrs_educ

age

female

south

west

cons

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