Group1_HW_Lab12.Rmd

---
title: "Group1_HW_Lab12"
output:
  word_document: default
  html_notebook: default
editor_options:
  chunk_output_type: inline
---

Consider Verizon data. Use the classical t-test to determine
whether the mean difference (Mean(ILEC)- Mean(CLEC) ) is
signicantly greater than zero. Are the assumptions met? Are
the population/true variances equal? Interpret the results.
```{r}
library(resampledata)
data("Verizon")

# head(Verizon)

dat=Verizon

ILEC=dat[dat$Group=="ILEC", ]
ILEC=ILEC$Time
CLEC=dat[dat$Group=="CLEC", ]
CLEC=CLEC$Time

#checking normality
qqnorm(ILEC)
qqline(ILEC)

qqnorm(CLEC)
qqline(CLEC)

t.test(Time~Group, data = Verizon, alt = "two.sided",var.equal = TRUE)

#OR

#TESTING EQUALITY OF VARIANCES
library(testequavar)
equa2vartest(ILEC, CLEC, 0.05, B=5000)

var(ILEC)
var(CLEC)

t.test(ILEC,CLEC, alt = "two.sided",var.equal = TRUE)



```
Since the pvalue is less than $\alpha$ we reject the null hypothesis that the true mean difference in repair times is significantly greater than zero.