This is an R Markdown Notebook. When you execute code within the notebook, the results appear beneath the code.

Try executing this chunk by clicking the Run button within the chunk or by placing your cursor inside it and pressing Cmd+Shift+Enter.

plot(cars)

Add a new chunk by clicking the Insert Chunk button on the toolbar or by pressing Cmd+Option+I.

When you save the notebook, an HTML file containing the code and output will be saved alongside it (click the Preview button or press Cmd+Shift+K to preview the HTML file).

rm(list = ls())
myDS <- read_excel("~/Documents/Onedrive/Social Entrepreneurship/Final Paper/socialvaluecreated.xlsx")
reg <- lm(SVC~bbyc_c+ctd, data = myDS)
summary(reg)

Call:
lm(formula = SVC ~ bbyc_c + ctd, data = myDS)

Residuals:
    Min      1Q  Median      3Q     Max 
-40.711 -11.502   3.135   9.220  37.031 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)  
(Intercept)  28.80076   24.70779   1.166   0.2664  
bbyc_c      -19.38657   12.60298  -1.538   0.1499  
ctd           0.03159    0.01456   2.169   0.0508 .
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 19.7 on 12 degrees of freedom
  (10 observations deleted due to missingness)
Multiple R-squared:  0.3002,    Adjusted R-squared:  0.1836 
F-statistic: 2.574 on 2 and 12 DF,  p-value: 0.1174
reg <- lm(SVC~cbyb_b+btd, data = myDS)
summary(reg)

Call:
lm(formula = SVC ~ cbyb_b + btd, data = myDS)

Residuals:
    Min      1Q  Median      3Q     Max 
-46.863 -12.269   3.728  13.250  30.689 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)  
(Intercept)   45.2207    23.3087   1.940   0.0762 .
cbyb_b      -282.0022   156.9956  -1.796   0.0977 .
btd            0.3718     0.2126   1.749   0.1058  
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 20.79 on 12 degrees of freedom
  (10 observations deleted due to missingness)
Multiple R-squared:  0.2202,    Adjusted R-squared:  0.09027 
F-statistic: 1.695 on 2 and 12 DF,  p-value: 0.2248
reg <- lm(SVC~cbyt_a+atd, data = myDS)
summary(reg)

Call:
lm(formula = SVC ~ cbyt_a + atd, data = myDS)

Residuals:
    Min      1Q  Median      3Q     Max 
-45.473 -12.046   3.846  13.771  31.799 

Coefficients:
             Estimate Std. Error t value Pr(>|t|)  
(Intercept)   47.7360    29.7712   1.603   0.1348  
cbyt_a      -394.3098   216.1655  -1.824   0.0931 .
atd            0.5077     0.2740   1.853   0.0887 .
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 20.52 on 12 degrees of freedom
  (10 observations deleted due to missingness)
Multiple R-squared:  0.2401,    Adjusted R-squared:  0.1135 
F-statistic: 1.896 on 2 and 12 DF,  p-value: 0.1925
reg <- lm(SVC~bbyt_d+dtd, data = myDS)
summary(reg)

Call:
lm(formula = SVC ~ bbyt_d + dtd, data = myDS)

Residuals:
    Min      1Q  Median      3Q     Max 
-41.948 -11.279   3.288  11.622  35.118 

Coefficients:
            Estimate Std. Error t value Pr(>|t|)  
(Intercept)  -9.0777   105.1054  -0.086   0.9326  
bbyt_d      -46.6103   146.7757  -0.318   0.7563  
dtd           0.1552     0.0720   2.155   0.0521 .
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 19.76 on 12 degrees of freedom
  (10 observations deleted due to missingness)
Multiple R-squared:  0.2958,    Adjusted R-squared:  0.1784 
F-statistic:  2.52 on 2 and 12 DF,  p-value: 0.122
corr()
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