HW 6

library(tidyverse)

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library(readxl)

library(readr)
Animal_Care_and_Control_Division_Annual_Statistics_1<-read_csv("Desktop/Applied Quantitative Methods/Animal_Care_and_Control_Division_Annual_Statistics-1.csv")

## Rows: 22 Columns: 17
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## Delimiter: ","
## dbl (17): Year, Number of Employees, Number of Division Vehicles, Annual Bud...
## 
## ℹ Use `spec()` to retrieve the full column specification for this data.
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Animalcare<-Animal_Care_and_Control_Division_Annual_Statistics_1

budget_model<-lm(`Annual Budget`~Year+`Number of Employees`+`Annual Adoption Revenue`,data=Animalcare)

summary(budget_model)

## 
## Call:
## lm(formula = `Annual Budget` ~ Year + `Number of Employees` + 
##     `Annual Adoption Revenue`, data = Animalcare)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -107218  -74341   -5378   42159  187820 
## 
## Coefficients:
##                             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)               -8.466e+07  1.046e+07  -8.095 2.07e-07 ***
## Year                       4.177e+04  5.377e+03   7.767 3.72e-07 ***
## `Number of Employees`      1.155e+05  2.694e+04   4.289 0.000442 ***
## `Annual Adoption Revenue` -1.436e+00  1.064e+00  -1.350 0.193814    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 88020 on 18 degrees of freedom
## Multiple R-squared:  0.961,  Adjusted R-squared:  0.9545 
## F-statistic: 147.8 on 3 and 18 DF,  p-value: 7.262e-13

plot(budget_model,which=1)

The independent variables: year, number of employees, and annual adoption revenue, have a close affect on the dependent variable since they could possibly determine the next year’s annual budget for the shelter. The model does meet the assumption of linearity.