## [1] 14.548
## [1] 2.779775
## [1] 18.34576
## [1] 10.72343
## [1]  6 20
## [1] 202
## [1] 40.4
## [1] 28.908

## 
## Call:
## lm(formula = S ~ ASVABC, data = df)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -6.3713 -1.7366 -0.1125  1.8222  6.7436 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)  14.1838     0.1093  129.78   <2e-16 ***
## ASVABC        1.6165     0.1178   13.72   <2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 2.371 on 498 degrees of freedom
## Multiple R-squared:  0.2742, Adjusted R-squared:  0.2728 
## F-statistic: 188.2 on 1 and 498 DF,  p-value: < 2.2e-16

## 
## Call:
## lm(formula = EARNINGS ~ S, data = df)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -17.177  -6.588  -2.147   3.532  86.424 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   3.0897     2.4638   1.254     0.21    
## S             1.0487     0.1664   6.304 6.41e-10 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10.33 on 498 degrees of freedom
## Multiple R-squared:  0.0739, Adjusted R-squared:  0.07204 
## F-statistic: 39.74 on 1 and 498 DF,  p-value: 6.407e-10
## [1] 19.8662
## 
## Call:
## lm(formula = EARNINGS ~ HEIGHT, data = df)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -17.316  -6.892  -2.783   4.070  80.276 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)  
## (Intercept)  -0.5133     7.9723  -0.064   0.9487  
## HEIGHT        0.2772     0.1170   2.370   0.0182 *
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 10.67 on 498 degrees of freedom
## Multiple R-squared:  0.01115,    Adjusted R-squared:  0.009166 
## F-statistic: 5.616 on 1 and 498 DF,  p-value: 0.01818

answers 1-10 1 Lines 12-21 The variables EARNINGS and S respectively represent the hourly wage someone earns while S represents the number of year of schooling an individual went through Mean of Earnings: 18.34576 dollars/hour Standard deviation of Earnings: 10.72343 dollars/hour Mean of S: 14.548 years of schooling Standard deviation of S: 2.779775 years of schooling 2 Lines 23 in order to compute the min and maximum value of years of schooling i used the range function and found that the minimum was six and max was 20 3 Lines 25-31 The percent of people in this sample that are married is 40.4 percent 4 Lines 34-36 The average age of individuals in this sample is 28.908 years old 5 Line 39 Line 39 in the code 6 Lines 41-42 The parameter of ASVABC is 1.6165 this means that for one increase in ASVABC s increases by 1.6165. The R^2 statistic is .2742. Lines 41-42 7 Lines 44-52

8 Lines 54-55 in the code the parameter for s is 1.0487. Meaning that for ever one increase in S Earnings increase by 1.0487. The R^2 Statistic is .0739. 9 Lines 57-59 predicted Earnings for someone with 16 years of schooling is 19.8662 dollars/hour 10 lines 61-62 The estimated parameter for HEIGHT is .2772. Meaning for every one increasing in height (in this case in inches) Earnings increases by .2772. The R^2 Statistic is .01115.