** Assignment 5: Tests for Comparing Group Means (t-Test). **Answer the following questions in complete sentences and using APA style. Upload to the Assignments section in Sakai.

*Note: You will have to choose which test is the correct one to run for each problem, which means that if you choose incorrectly you will not receive any points for that question, even if your process is correct and answers are in APA style. So if you have any doubts, feel free to consult with me as you work on your assignment. You will not have an opportunity to revise your work after you submit your assignment, so I encourage you to ask questions as you need to.*

- List common assumptions for tests of mean differences and discuss why it is important to check them. (Hint: there are two for both independent and dependent tests, and two more for just independent tests.) You will be expected to test these assumptions for each of the scenarios below, so if you have any questions on these assumptions, post them on Sakai.
**(.7 pt)** - An admission staff is making comparison between sample mean ACT score and a known population mean ACT score.
*ACT_Summer 2016.sav*contains the data for #2. (Assumes that the average ACT score for IL is known for 20.9.)- Write the null and alternative hypotheses.
**(.2 pt)** - Which is the most appropriate statistical test to run and why?
**(.5 pt)** - Manually calculate the test statistic. Which equation you use will depend on which test you chose in part b. For data that you need (i.e. sample mean and standard deviation) you can calculate them manually, or run them using the descriptive statistics tests you worked with in Assignment 2.
**(1 pt)** - Run the most appropriate test and copy and paste the output table(s) into your assignment.
**(.5 pt.)** - Does your test statistic from part c match your test statistic in the SPSS output table in part d? If so, then you are on the right track. If not, then check your calculations and make sure you ran your SPSS test correctly.
- Report the findings in APA style. Don’t forget to calculate the effect size. (Follow the instructions in Ch. 11 on how to do this.)
**(1 pt)**

- Write the null and alternative hypotheses.
- A nurse practitioner wants to compare differences between control and experimental group on the effectiveness in treating constipation.
*Constipation_Summer 2016.sav*contains the data for #3.- Write the null and alternative hypotheses.
**(.2 pt)** - Which is the most appropriate statistical test to run and why?
**(.5 pt)** - Manually calculate the test statistic. Which equation you use will depend on which test you chose in part b.
**(1 pt)** - Run the most appropriate test and copy and paste the output table(s) into your assignment.
**(0.5 pt.)** - Does your test statistic from part c match your test statistic in the SPSS output table in part d? If so, then you are on the right track. If not, then check your calculations and make sure you ran your SPSS test correctly.
- Report the findings in APA style. (Follow the instructions in Ch. 11 on how to do this.)
**(1 pt)**

- Write the null and alternative hypotheses.
- A nurse manager wants to compare differences in safety culture scores from respondents in accredited nursing homes across two time points.
*Safety_Summer 2016.sav*contains the data for #4.- Write the null and alternative hypotheses.
**(.2 pt)** - Which is the most appropriate statistical test to run and why?
**(.5 pt)** - Manually calculate the test statistic. Which equation you use will depend on which test you chose in part b.
**(1 pt)** - Run the most appropriate test and copy and paste the output table(s) into your assignment.
**(0.5 pt.)** - Does your test statistic from part c match your test statistic in the SPSS output table in part d? If so, then you are on the right track. If not, then check your calculations and make sure you ran your SPSS test correctly.
- Report the findings in APA style. (Follow the instructions in Ch. 11 on how to do this.)
**(1 pt)**

- Write the null and alternative hypotheses.
- So far, we have only compared two groups, so we have used t-tests. However, when your independent variable (also called the grouping variable) has more than two groups, you need to use a One-Way ANOVA test to compare these multiple groups. In this scenario, a nurse researcher is examining whether the amount of exercise (None, 1 time per week, 2 times per week, and more than 2 times per week) has any influence on personal satisfaction.
*Satisfaction_Summer 2016.sav*contains the data for #5.- Write the null and alternative hypotheses.
**(.2 pt)** - Run a one-way ANOVA test and copy and paste your output tables here.
**(.5 pt)** - Report the findings in APA style. Don’t forget to calculate and report the effect size. (Follow the instructions in Ch. 11 on how to do this.)
**(1 pt)** - If the one-way ANOVA does find a significant difference between groups, then the next step is to determine which groups are differ and by how much. To do this, we need to run a post hoc test. There are many post hoc tests, so you need to decide which test is the best to run based on the data. (Hint: Thoroughly read the section on post hoc tests in Ch. 11 of your book. Which is the most appropriate post hoc test to run and why?
**(1 pt)** - Run the most appropriate post hoc test and copy and paste your output tables here.
**(.5 pt)** - Report the findings in APA style. (Follow the instructions in Ch. 11 on how to do this.) A post hoc test will have multiple comparisons to consider, so you will have multiple significance levels to report.
**(1.5 pt)**

- Write the null and alternative hypotheses.