Write a short function that could be used to test whether the observations of a categorical variable are uniformly distributed (meaning all probabilities are equal across categories). (Hint: you can test whether the function works by testing whether the distribution of risk is 1/3:1/3:1/3). Begin the function with the following template:
my.chi.test <- function (x){
#created function goes here
return( list=c("X-squared" = chi, "df" = length(x)-1,
"p-value" = round(value,4)))

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my.chi.test <- function (x){
   #created function goes here
x <- mtcars$gear   
   # get unique values
   distinct_categories <- unique(x)
   # count number of unique values
   category_cnt <- length(distinct_categories)
   # Expected probability
   expected_prob <- 1/category_cnt
   # expected count
   expected_cnt <- length(x) * expected_prob...

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