Answer:
Step-by-step explanation:
Given that:
Mean μ= 100
standard deviation σ = 2.6
sample size n = 9
sample mean X = 100.6
The null hypothesis and the alternative hypothesis can be computed as follows:
[tex]H_o : \mu \leq 100[/tex]
[tex]H_1 :\mu > 100[/tex]
The numerical value for the test statistics is :
[tex]z = \dfrac{x - \mu}{\dfrac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \dfrac{100.6- 100}{\dfrac{2.6}{\sqrt{9}}}[/tex]
[tex]z = \dfrac{0.6}{0.8667}[/tex]
z = 0.6923
At ∝ = 0.05
[tex]t_{\alpha/2 } = 0.025[/tex]
The critical value for the z score = 0.2443
From the z table, area under the curve, the corresponding value which is less than the significant level of 0.05 is 1.64
P- value = 0.244
c> If the true population mean is 101.3 ;
Then:
[tex]z = \dfrac{x - \mu}{\dfrac{\sigma}{\sqrt{n}}}[/tex]
[tex]z = \dfrac{101.3- 100.6}{\dfrac{2.6}{\sqrt{9}}}[/tex]
[tex]z = \dfrac{0.7}{0.8667}[/tex]
z = 0.808
From the normal z tables
P value = 0.2096