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The average stress score of students in online universities
QUESTION
Suppose you have information that the average stress score of students in online universities is 13.15.
Using Microsoft Excel, compute a one-sample t-test to find out whether the stress scores reported by your sample are significantly different from those of the population of online students.
Move your output into a Microsoft Word document.
Write one paragraph to explain how you located and determined the critical value of t, and how you determined whether your obtained t-statistic was significant.
Subject | Education Systems | Pages | 2 | Style | APA |
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Answer
One Sample T-Test
Population Mean (): 21
Sample Mean (): 13.15
Sample Standard Deviation (s): 7.160577171
Sample size (n): 72
t= = -9.302247179
1.994
BCR: Reject given that |t| >
|t| = 9.302247179
9.302247179 > 1.994
In locating the critical value of t, I used the student-t distribution table. I majorly used two metrics (the degree of freedom of the sample and which is the significance level) from Engineering Statistics Handbook (u.d). Given that this type of test was two-tailed-given the hypothesis, I used the two-tailed tests. The degree of freedom was gotten using n-1 (72-1) which gave 71. So, in the t-table, I chose 70 as the closest degrees of freedom and checked vertically along the 5% significance level. This gave me the value 1.994. To assess whether my calculated t was significant, I applied the Basic Critical Region (BCR) Test which states that Reject given that |t| > according to Test (2018)
The obtained t (9.3) falls within the rejection region given by the critical t (1.994)Therefore, at 5% level of significance, we reject the null hypothesis and conclude that there is enough evidence to show that stress scores reported in the Week 6 sample are significantly different from those of the population of online students.
References
Engineering Statistics Handbook. 1.3.6.7.2. Critical Values of the Student’s-t Distribution. Itl.nist.gov. Retrieved 27 April 2021, from https://www.itl.nist.gov/div898/handbook/eda/section3/eda3672.htm. Test, N., Plot, T. S., & Plot, I. V. (2018). One-sample t-test.
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