Model_1<-lm(`Tax Code Ch. 351 Revenue`~`Advertising Revenue`,data = Hot)
summary(Model_1)
##
## Call:
## lm(formula = `Tax Code Ch. 351 Revenue` ~ `Advertising Revenue`,
## data = Hot)
##
## Residuals:
## Min 1Q Median 3Q Max
## -47374631 -1945553 -1893153 -1722524 1654749672
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 1.909e+06 1.268e+06 1.505 0.133
## `Advertising Revenue` 3.248e+00 4.762e-01 6.821 1.3e-11 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 48330000 on 1509 degrees of freedom
## (884 observations deleted due to missingness)
## Multiple R-squared: 0.02991, Adjusted R-squared: 0.02927
## F-statistic: 46.53 on 1 and 1509 DF, p-value: 1.304e-11
plot(Model_1,which = 1)
#linear (add extra verbiage)
library(lmtest)
## Warning: package 'lmtest' was built under R version 4.4.2
## Loading required package: zoo
## Warning: package 'zoo' was built under R version 4.4.2
##
## Attaching package: 'zoo'
## The following objects are masked from 'package:base':
##
## as.Date, as.Date.numeric
dwtest(Model_1)
##
## Durbin-Watson test
##
## data: Model_1
## DW = 2.0007, p-value = 0.4986
## alternative hypothesis: true autocorrelation is greater than 0
#No violation
plot(Model_1, which = 3)
#fairly homoscedasitc
plot(Model_1, which = 2)
#Normally distributed
library(car)
## Loading required package: carData
##
## Attaching package: 'car'
## The following object is masked from 'package:dplyr':
##
## recode
## The following object is masked from 'package:purrr':
##
## some
#Yes, my model meets all assumptions. VIF did not run because a lack of variables.
#My Model did not violate any assumptions, so mitigation was not needed.