library(tidyverse)
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## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors
library(readxl)


data<-read_excel("district.xls")
model1<-lm(DA0AT21R~DPETLEPP+DPETGIFP,data=data)

summary(model1)
## 
## Call:
## lm(formula = DA0AT21R ~ DPETLEPP + DPETGIFP, data = data)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -96.189  -0.711   0.586   1.656   5.724 
## 
## Coefficients:
##              Estimate Std. Error t value Pr(>|t|)    
## (Intercept) 94.260072   0.241673 390.031  < 2e-16 ***
## DPETLEPP     0.002292   0.009578   0.239  0.81092    
## DPETGIFP     0.083692   0.026795   3.123  0.00183 ** 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 4.85 on 1200 degrees of freedom
##   (4 observations deleted due to missingness)
## Multiple R-squared:  0.008074,   Adjusted R-squared:  0.006421 
## F-statistic: 4.884 on 2 and 1200 DF,  p-value: 0.00772

Question 5) The overall model explains that the dependent variable is effected by the number of gifted and talented students. The significant variable is DPETGIFP The insignificant varaibles is DPETLEPP Question 6) When the number of gifted and talented students increase in the district so do the various assessment scores or performance indicators for the year. Question 7)Violates the assumption of linearity

plot(model1, which = 1)

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