Nishishiba et al. (2013) explain in chapter 9 that “T-tests are the statistical tests you can use when you have a research question that requires a comparison of two means. This requires a d
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Assignment No. 1
One (1) original post and two (2) response posts are required for each discussion.
The original post (or initial post) must be posted at least a week before the module due date. Points will be deducted for original posts that are posted late, as this impacts the quality of an interactive discussion.
Please adhere to the following posting guidelines:?
Edit your writing prior to submission.
Analyze the topic and content. This is not an opinion piece.
Compare/Contrast the videos/film to the readings and/or course content (when applicable).
Advance the conversation in the response posts.
Support your position with sources. Use the APA format.
Provide three (3) posts
Remember this is an exercise in academic writing.
To state that you agree or disagree with a classmate is not adequate for a college level research course.?
Keep in mind that your discussion forum postings will be seen by other members of the course. Care should be taken when determining what to post.
Discussion Prompt
Nishishiba et al. (2013) explain in chapter 9 that “T-tests are the statistical tests you can use when you have a research question that requires a comparison of two means. This requires a dependent variable that is a continuous measure.”
When comparing means, why is it important to perform a t-test rather than just looking at the differences in the means? How would you explain this to a policymaker? (see pages 174-175)
?
And now for the debate ..
One of the assumptions of the T-test is that “the variable from which the mean is calculated must be normally distributed. If there is a sample size of less than 15, then the … t-test is not an appropriate choice as outliers heavily influence the data” (Nishishiba et al., 2013, p.176).
So, let’s say you have a sample size of 15 employees each in two groups. Can you use a T-test to detect statistical difference in the mean job satisfaction level of the two groups? Or should you never, ever use a T-test with a sample size that is less than 40? Is there even a minimum sample size? Explain. (see assumptions of T-test pages, 176, 178, and 186).
Assignment No. 2
Please see Attached Excel Attachment
Run an independent samples t-test by using Microsoft Excel. Here are the steps:
1. ? After opening?, click on the Data tab near the top of the screen and select Data Analysis.
2. ? You will see the option for three different t-tests.
3. ? Excel does not allow you to test for homogeneity of variances; therefore, you must make an assumption. If you are unsure whether your variances are equal, it is always better to be a little more conservative and use the assumption of unequal variances. In this case,?choose t-test: Two-Sample Assuming Unequal Variances.
4. ? To test for a difference in the morality raw gain, fill in the data as shown in the box below:
Variable 1 range has the cells G3 through G6. These represent the raw mortality gain scores for the alternative delivery service group. Variable 2 range is the array that you are comparing array 1 against. In this case, cells G7 through G10, represent the raw mortality gain scores for the traditional service delivery group. Clicking on output range allows you to place the output within the worksheet.
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Submit your work and answer the following questions?
1. Upload your “Independent samples t-test” output table here using the upload option.
2. ?One of the assumptions of the t-test is that the variable from which the mean is calculated must be normally distributed. Under what conditions can this assumption be violated?
3. Refer to your t-test output table, do traditional delivery fire stations in the Rockwood Fire Department have statistically different mortality and cost per call gain scores than alternative delivery stations?
(Please do not send responses as text entry; use the file upload option. You can upload more than one file.)
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