dat95 <- c(5.263,6.748,7.461,7.015,8.133,7.418,3.772,8.963)
dat100 <- c(11.176,7.089,8.097,11.739,11.291,10.759,6.467,8.315)
dat<-data.frame(dat95,dat100)
boxplot(dat95,dat100,col=c("light blue","red"),names=c("thickness1","thickness2"))

size of the box is not same it means the varience are different.

t.test(dat95,dat100,alternative = "greater")
## 
##  Welch Two Sample t-test
## 
## data:  dat95 and dat100
## t = -2.6751, df = 13.226, p-value = 0.9906
## alternative hypothesis: true difference in means is greater than 0
## 95 percent confidence interval:
##  -4.186071       Inf
## sample estimates:
## mean of x mean of y 
##  6.846625  9.366625

the value of p is 0.9906 which is more than the 0.05 is the evidence to support the claim that the higher baking temperature results in wafers with a lower

#mean photoresist thickness

t.test(dat95,dat100,alternative = c("two.sided","less","greater"))

confidence interval -4.5515722 -0.4884278

library(dplyr)
## 
## Attaching package: 'dplyr'
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
qqnorm(dat95, main = "thickness1")
qqline(dat95)

qqnorm(dat100, main= "thickness2")
qqline(dat100)

### the normal probability plot does not falls in stright line so its not normally distributed.

dat95 <- c(5.263,6.748,7.461,7.015,8.133,7.418,3.772,8.963)
dat100 <- c(11.176,7.089,8.097,11.739,11.291,10.759,6.467,8.315)
dat<-data.frame(dat95,dat100)
boxplot(dat95,dat100,col=c("light blue","red"),names=c("thickness1","thickness2"))
t.test(dat95,dat100,alternative = "greater")
t.test(dat95,dat100,alternative = c("two.sided","less","greater"))
library(dplyr)
qqnorm(dat95, main = "thickness1")
qqline(dat95)
qqnorm(dat100, main= "thickness2")
qqline(dat100)