Homework 7

library(readxl)
district <- read_excel("district.xls")
library(tidyverse)

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library(pastecs)

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library(lmtest)

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library(MASS)

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data_multiple <- lm(DA0CT21R  ~ DA0AT21R + DPETECOP, data = district)

plot(data_multiple,which=1)

raintest(data_multiple)

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##  Rainbow test
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## data:  data_multiple
## Rain = 1.018, df1 = 541, df2 = 537, p-value = 0.418

library(car)

## Loading required package: carData

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durbinWatsonTest(data_multiple)

##  lag Autocorrelation D-W Statistic p-value
##    1      0.02736478      1.941079   0.304
##  Alternative hypothesis: rho != 0

plot(data_multiple,which=3)

bptest(data_multiple)

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##  studentized Breusch-Pagan test
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## data:  data_multiple
## BP = 59.993, df = 2, p-value = 9.388e-14

plot(data_multiple,which=2)

shapiro.test(data_multiple$residuals)

## 
##  Shapiro-Wilk normality test
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## data:  data_multiple$residuals
## W = 0.98053, p-value = 7.466e-11

vif(data_multiple)

## DA0AT21R DPETECOP 
## 1.152022 1.152022

Explanation The model does meet the assumptions as the p-value of 0.418 is >0.05 which we can assume there is linearity of this model.The model does violate the homoscedasticity assumption. How to mitigate this wouls be to use a log transformation