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--- c:ma:2019:multiple_regression_exercise [2019/11/08 10:46] – [Ex. 2] hkimscil
+++ c:ma:2019:multiple_regression_exercise [2019/11/08 10:51] – [Ex. 2] hkimscil
@@ Line 106: / Line 106: @@
 Multiple R-squared:  0.3943,	Adjusted R-squared:  0.3912
 F-statistic: 128.2 on 2 and 394 DF,  p-value: < 2.2e-16
+> </code>
+<code>> summary(lm.sal.many)
+Call:
+lm(formula = salary ~ yrs.service + rank + discipline + sex,
+    data = Salaries)
+Residuals:
+   Min     1Q Median     3Q    Max
+-64202 -14255  -1533  10571  99163
+Coefficients:
+              Estimate Std. Error t value Pr(>|t|)
+(Intercept)   68351.67    4482.20  15.250  < 2e-16 ***
+yrs.service     -88.78     111.64  -0.795 0.426958
+rankAssocProf 14560.40    4098.32   3.553 0.000428 ***
+rankProf      49159.64    3834.49  12.820  < 2e-16 ***
+disciplineB   13473.38    2315.50   5.819 1.24e-08 ***
+sexMale        4771.25    3878.00   1.230 0.219311
+---
+Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
+Residual standard error: 22650 on 391 degrees of freedom
+Multiple R-squared:  0.4478,	Adjusted R-squared:  0.4407
+F-statistic: 63.41 on 5 and 391 DF,  p-value: < 2.2e-16
 > </code>