Capstone_Dataset_Barnes

Capstone_Dataset <-read_csv("Capstone_Dataset.csv")

## Rows: 1184 Columns: 21
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr  (1): DISTNAME
## dbl (20): TOT_EXP, SSS_PROP, GCS_PROP, SS_PROP, CS_PROP, SSS_DA, GSC_DA, SS_...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.

cor(Capstone_Dataset$SSS_PROP,Capstone_Dataset$OVERALL_SCORE, method = "pearson")

## [1] 0.01323415

plot(Capstone_Dataset$SSS_PROP, Capstone_Dataset$OVERALL_SCORE)

model<-lm(Capstone_Dataset$OVERALL_SCORE~Capstone_Dataset$SSS_PROP+Capstone_Dataset$LEP_PROP+Capstone_Dataset$SPED_PROP+Capstone_Dataset$ECONDIS_PROP, data=Capstone_Dataset)

summary(model)

## 
## Call:
## lm(formula = Capstone_Dataset$OVERALL_SCORE ~ Capstone_Dataset$SSS_PROP + 
##     Capstone_Dataset$LEP_PROP + Capstone_Dataset$SPED_PROP + 
##     Capstone_Dataset$ECONDIS_PROP, data = Capstone_Dataset)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -32.979  -5.177   0.524   5.645  20.399 
## 
## Coefficients:
##                               Estimate Std. Error t value Pr(>|t|)    
## (Intercept)                   92.78190    1.08778  85.294  < 2e-16 ***
## Capstone_Dataset$SSS_PROP     -0.02323    0.14447  -0.161  0.87227    
## Capstone_Dataset$LEP_PROP      0.03111    0.01838   1.693  0.09077 .  
## Capstone_Dataset$SPED_PROP    -0.13592    0.05197  -2.615  0.00903 ** 
## Capstone_Dataset$ECONDIS_PROP -0.20832    0.01314 -15.851  < 2e-16 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 8.224 on 1179 degrees of freedom
## Multiple R-squared:  0.2098, Adjusted R-squared:  0.2071 
## F-statistic: 78.25 on 4 and 1179 DF,  p-value: < 2.2e-16