We have "\\mu_0=50"
For the sample, we have
"n=30, \\bar{X}=47" and
"S=5.5"
Null Hypothesis, "H_0:\\mu=\\mu_0"
Alternate hypothesis, "H_1:\\mu\\not=\\mu_0"
Test statistics, "t=(\\bar{x}-\\mu_0)\/(S\/\\sqrt{n})"
"=(47-50)\/(5.5\/\\sqrt{30})"
"=-3\/1.004=-2.9875"
Since the population standard deviation is unknown and the sample size is also small, we will use t-test.
Degree of freedom (DOF) for this t-test will be equal to "n-1=30-1=29" .
The t-critical values for a two-tailed test, for a significance level of "\\alpha= 0.05" and "DOF=29" will be
"t_c<-2.045" and "t_c>2.045".
As we can see that our test statistics lies in the critical region, we will have to reject the null hypothesis.
So, we can say that at "\\alpha =0.05" the advertiser's statement is false.
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