A budget head for SSS Sales Inc. would like to compare the daily travel expenses for the sales staff and the audit staff. He collected the following sample information.
Sales Staff
105
120
140
160
100
170
160
140
130
160
180
190
Audit Staff
130
50
90
80
70
125
180
80
110
At 0.05 significance level, can he conclude that the mean daily expenses of sales staff are greater than the audit staff?
Let "\\mu_1" be the sample mean for population 1 (sales staff) and "\\mu2" be the sample mean for population 2(audit staff) then, the hypothesis tested is,
"H_0:\\mu_1=\\mu_2"
"Against"
"H_1:\\mu_1\\gt\\mu_2"
To perform this hypothesis test we shall use the "p-value" technique the compare this value with the given "\\alpha =0.05" level of significance.
By applying the 2 sample t-test in "R" we can easily perform the test using the commands below,
x=c(105,120,140,160,100,170,160,140,130,160,180,190)
y=c(130,50,90,80,70,125,180,80,110)
t. test(x, y)
The output for these commands are as shown below.
Welch Two Sample t-test
data: x and y
t = 2.8812, df = 14.066, p-value = 0.01204
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
11.40976 77.75691
sample estimates:
mean of x mean of y
146.2500 101.6667
From this output the "p-value" is divided by 2 since we are performing a one sided test thus, "p-value=0.01204\/2=0.00602" and reject the null hypothesis if "p-value\\lt\\alpha"
Since "p-value=0.00602\\lt\\alpha=0.05," we reject the null hypothesis and conclude that evidence exist to show that the mean daily expenses of sales staff are greater than the audit staff.
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