This week, we are looking at inferences about samples taken from the


This week, we are looking at inferences about samples taken from the population using hypothesis testing. We study several different hypothesis tests in the class, including normal distribution, t-Test, Chi-Square equal frequencies, Chi-Square unequal frequencies, Chi-Square independence, and Analysis of Variance (ANOVA). In this discussion we will perform a t test. A t-test is used when you have a normal distribution, a quantitative variable, and the population mean is not known. 

To prepare for this Discussion:

  • Review the following resources:

Discussion Resources (click to expand/reduce)

  • Look at the data set that you used in Discussion 1 or 2.  In order to do this week’s Discussion, you will need to have one quantitative variable that you want to test against some widely accepted value.

Example: (click to expand/reduce)

  • Review the rubric that will be used for grading.  

With these thoughts in mind:

By Day 1

By the end of Day 1 you can post your scenario and data for your Instructor to review. If you do not submit this by the end of Day 1, you will need to proceed to submit the entire Discussion on Day 3.

By Day 3

Post a 1- to 2-paragraph write-up that includes the following:

  1. You will want to use Word for your Discussion post.
  2. Include your data set and describe the scenario you will be using for the hypothesis test. Give the null and alternative hypotheses and your level of significance. In your hypotheses, how did you determine what value to test against?
  3. Enter the data for your quantitative variable in the Statdisk Sample Editor.
  4. Choose Analysis, Hypothesis Test, Mean- One Sample. Click on the Use data at the top of the menu. If you want to use a different level of significance, change that value. Paste your complete Statdisk results in your Discussion.
    Note: The information for the alternative hypothesis at the top of the menu must agree with your alternative hypothesis (equal, not equal, greater than, less than). For my example, I would need to change the menu to “greater than.” Click on Evaluate and paste your results into the document.
  5. Write a conclusion statement based on your comparison of the p-value and level of significance. The prescribed format is: Since the p-value of # is more/less than the level of significance of #, the null hypothesis is/is not rejected; therefore, the data supports (paraphrase the hypothesis supported).
  6. What is the most important thing that you learned from this Discussion post, and why?

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