R Notebook

               Df Sum Sq Mean Sq F value Pr(>F)    
X1SEX           1   5102    5102    2911 <2e-16 ***
Residuals   20208  35416       2                   
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

                Df Sum Sq Mean Sq F value Pr(>F)    
X3HSCOMPSTAT     4    267   66.73    33.5 <2e-16 ***
Residuals    20205  40251    1.99                   
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

              Df Sum Sq Mean Sq F value   Pr(>F)    
S3WORKFT       2    123   61.69   30.08 9.59e-14 ***
Residuals   8766  17981    2.05                     
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

              Df Sum Sq Mean Sq F value   Pr(>F)    
S3CURJOBFT     2     29  14.611   8.783 0.000155 ***
Residuals   8035  13368   1.664                     
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

                  Df Sum Sq Mean Sq F value Pr(>F)    
P1INCOMECATBIN     9    335   37.21    19.8 <2e-16 ***
Residuals      14644  27526    1.88                   
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

                  Df Sum Sq Mean Sq F value Pr(>F)    
X1FAMINCOMEBIN     9    355   39.40   21.02 <2e-16 ***
Residuals      15540  29131    1.87                   
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

                  Df Sum Sq Mean Sq F value Pr(>F)    
X2FAMINCOMEBIN     9    292   32.46   16.59 <2e-16 ***
Residuals      17907  35043    1.96                   
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

               Df Sum Sq Mean Sq F value Pr(>F)    
X1RACE          7    249   35.59   17.86 <2e-16 ***
Residuals   20202  40269    1.99                   
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

#PLOT data

#Plot both data

#Linear regression 2 types for weighted GPA

Call:
lm(formula = S1HRVIDEO ~ X3TAGPAWGT, data = gpa_weighted)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.5631 -0.8773 -0.6030  0.2598  4.8084 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)    
(Intercept)  2.70022    0.03337   80.91   <2e-16 ***
X3TAGPAWGT  -0.13715    0.00491  -27.93   <2e-16 ***
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.389 on 18833 degrees of freedom
Multiple R-squared:  0.03978,   Adjusted R-squared:  0.03973 
F-statistic: 780.1 on 1 and 18833 DF,  p-value: < 2.2e-16

#Linear Regressions for Total GPA

Call:
lm(formula = S1HRVIDEO ~ X3TGPATOT, data = GPA_total)

Residuals:
    Min      1Q  Median      3Q     Max 
-1.6678 -0.8843 -0.5708  0.2724  4.5859 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)    
(Intercept)  2.824529   0.039469   71.56   <2e-16 ***
X3TGPATOT   -0.156710   0.005902  -26.55   <2e-16 ***
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Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 1.391 on 18848 degrees of freedom
Multiple R-squared:  0.03605,   Adjusted R-squared:  0.036 
F-statistic:   705 on 1 and 18848 DF,  p-value: < 2.2e-16