Week 6 Discussion

Observed
myvector=c(348,52) 
mymatrix=matrix(c(348,52,0,0), nrow=2)
colnames(mymatrix) <- c("Grad", "NoGrad")
rownames(mymatrix) <-c("Job", "NoJob")
mymatrix
##       Grad NoGrad
## Job    348      0
## NoJob   52      0
Expected
myvector2=c(200,200) 
mymatrix2=matrix(c(200,200,200,200), nrow=2)
colnames(mymatrix2) <- c("Grad", "NoGrad")
rownames(mymatrix2) <-c("Job", "NoJob")
mymatrix2
##       Grad NoGrad
## Job    200    200
## NoJob  200    200
Ho: Getting a job is independent of graduating.
Ha: Getting a job is not independent of graduating.

df = (r-1)(c-1) = (2-1)(2-1)=1

alpha = .01

Chi-Square(1,.01) = 6.635

If Chi > 6.635 Reject Ho

If Chi <= 6.635 Do not Reject Ho

Chi Square Value = [(348-200)^2/200]+[(52-200)^2/200] = 219.04

219.04 > 6.635

Reject the null hypothesis that getting a job is independent of graduating.

chisq.test(mymatrix)
## Warning in chisq.test(mymatrix): Chi-squared approximation may be incorrect
## 
##  Pearson's Chi-squared test
## 
## data:  mymatrix
## X-squared = NaN, df = 1, p-value = NA