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library(tidyverse)
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library(pastecs)
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library(lmtest)
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library(MASS)
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library(car)
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library(ggplot2)
Animal_Control<-read_csv("Animal_Care_and_Control_Division_Annual_Statistics.csv")
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## dbl (17): Year, Number of Employees, Number of Division Vehicles, Annual Bud...
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Animal_Control<- Animal_Control %>% drop_na(Adoptions)
Animal_Control <- Animal_Control %>% drop_na(`Return to Owner`)
Animal_Control <- Animal_Control %>% drop_na(`Fostered Animals`)
hist(Animal_Control$Adoptions)
hist(Animal_Control$`Return to Owner`)
hist(Animal_Control$`Fostered Animals`)
hist(Animal_Control$Euthanized)
ggplot(Animal_Control,aes(x=Adoptions,y=Euthanized)) + geom_point() + labs(title="Adoptions vs Euthanized",subtitle = "From the Animal_Care_and_Control_Division_Annual_Statistics Dataset - R (2026)")
ggplot(Animal_Control,aes(x=`Return to Owner`,y=Euthanized)) + geom_point() + labs(title="Return to Owner vs Euthanized",subtitle = "From the Animal_Care_and_Control_Division_Annual_Statistics Dataset - R (2026)")
ggplot(Animal_Control,aes(x=`Fostered Animals`,y=Euthanized)) + geom_point() + labs(title="Fostered Animals vs Euthanized",subtitle = "From the Animal_Care_and_Control_Division_Annual_Statistics Dataset - R (2026)")
Adoptions_RTO_Foster <- lm(Euthanized~Adoptions+`Fostered Animals`+`Return to Owner`, data=Animal_Control)
summary(Adoptions_RTO_Foster)
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## Call:
## lm(formula = Euthanized ~ Adoptions + `Fostered Animals` + `Return to Owner`,
## data = Animal_Control)
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## Residuals:
## Min 1Q Median 3Q Max
## -754.1 -272.6 108.0 255.5 486.0
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## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 3576.9917 1121.0412 3.191 0.005353 **
## Adoptions -1.9252 0.4290 -4.488 0.000324 ***
## `Fostered Animals` -0.1896 0.2593 -0.731 0.474530
## `Return to Owner` 2.9390 1.8206 1.614 0.124861
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
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## Residual standard error: 391.9 on 17 degrees of freedom
## Multiple R-squared: 0.6974, Adjusted R-squared: 0.644
## F-statistic: 13.06 on 3 and 17 DF, p-value: 0.0001133
Adoptions_RTO_Foster <- lm(Euthanized~Adoptions+`Fostered Animals`+`Return to Owner`, data=Animal_Control)
plot(Adoptions_RTO_Foster,which=1)
raintest(Adoptions_RTO_Foster)
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## data: Adoptions_RTO_Foster
## Rain = 8.1043, df1 = 11, df2 = 6, p-value = 0.009022
Adoptions_RTO_Foster<-lm(Euthanized~Adoptions+`Fostered Animals`+`Return to Owner`, data=Animal_Control)
Adoptions_RTO_Foster_log<-lm(log(Euthanized)~log(Adoptions+`Fostered Animals`+`Return to Owner`),data=Animal_Control)
plot(Adoptions_RTO_Foster_log,which=1)
raintest(Adoptions_RTO_Foster_log)
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## data: Adoptions_RTO_Foster_log
## Rain = 4.5353, df1 = 11, df2 = 8, p-value = 0.02055
durbinWatsonTest(Adoptions_RTO_Foster)
## lag Autocorrelation D-W Statistic p-value
## 1 0.1800719 1.569375 0.148
## Alternative hypothesis: rho != 0
plot(Adoptions_RTO_Foster,which = 3)
bptest(Adoptions_RTO_Foster)
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## studentized Breusch-Pagan test
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## data: Adoptions_RTO_Foster
## BP = 1.2035, df = 3, p-value = 0.7522
plot(Adoptions_RTO_Foster,which=2)
shapiro.test(Adoptions_RTO_Foster$residuals)
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## Shapiro-Wilk normality test
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## data: Adoptions_RTO_Foster$residuals
## W = 0.94478, p-value = 0.2704
plot(Adoptions_RTO_Foster_log,which=2)
Adoptions_RTO_Foster <- lm(Euthanized~Adoptions+`Fostered Animals`+`Return to Owner`, data=Animal_Control)
vif(Adoptions_RTO_Foster)
## Adoptions `Fostered Animals` `Return to Owner`
## 1.470658 1.661375 1.226752