You wish to test the following claim ($\displaystyle {H}_{{a}}$) at a significance level of $\displaystyle \alpha={0.10}$.      

$\displaystyle {H}_{{o}}:\mu={75.4}$
$\displaystyle {H}_{{a}}:\mu>{75.4}$

You believe the population is normally distributed, but you do not know the standard deviation.

Data
74.9
93.3
91.9
96.2
35.5
69.7
80.0
60.0
110.2
69.7
70.8
71.3
97.1
48.6
81.6
60.0
76.5
56.9
62.0
84.7
76.5
69.7
84.7
124.0
62.7
74.9
66.4
80.0
60.7
39.0
73.9
30.0
62.7
62.7
53.2
60.0
68.1
104.0
88.1
99.7
98.8
65.2
48.6
30.0
108.4
97.1
78.5
69.7
83.1
115.0
80.5
85.9
70.8
88.1
39.0
78.5
86.4
77.5
54.2
63.3

Use StatCrunch.

• Copy and paste the data into an empty column in Statcrunch
• Select Stat → T Statistics → One Sample → From data
• Select the column the data is in
• Enter the appropriate null claim and alternative hypothesis. 
• Press Compute!

1. What is the test statistic for this sample?
   
   test statistic = Round to 3 decimal places
   
   
2. What is the p-value for this sample?
   
   p-value = Use Technology Round to 4 decimal places.
   
   
3. The p-value is...
   • less than (or equal to) $\displaystyle \alpha$
   • greater than $\displaystyle \alpha$
   
   
   
4. This test statistic leads to a decision to...
   
   • reject the null
   • accept the null
   • fail to reject the null
   
   
   
5. As such, the final conclusion is that...
   
   • There is sufficient evidence to warrant rejection of the claim that the population mean is greater than 75.4.
   • There is not sufficient evidence to warrant rejection of the claim that the population mean is greater than 75.4.
   • The sample data support the claim that the population mean is greater than 75.4.
   • There is not sufficient sample evidence to support the claim that the population mean is greater than 75.4.