Using Minitab Statistics to calculate the various T-Tests
The steps required for completing the deliverables for this assignment (screen shots that correspond to these instructions can be found immediately following them).Complete the questions below and paste the answers from Minitab below each question (type your answers to the questions where noted). Therefore, your response to the lab will be this ONE document submitted to the Dropbox.
Context (remember that statistics are far more than numbers or values - you need to know the context to perform a good analysis!).
Independent Samples: Patients diagnosed with depression according to the Beck Depression Inventory are randomly assigned to receive a Placebo vs. Lexapro for their treatment. Reassessment occurs at four weeks.
Note: Moderate Depression is indicated by a score of 21 or more when using the Beck Depression Inventory. Patients scoring 30 or more would not qualify for this study as they would need more intense treatment and would not be given a placebo.
Paired Sample T-Test: Assess the effectiveness of the hospital's diabetic education program by comparing preteaching and postteaching test scores for new diabetics on disease management.
Note: These patients cannot be discharged until they pass their posttest and insurance typically will not pay for the hospital stay if they leave against medical advice (AMA).
View the Minitab tutorial on T-Tests. The 2-Sample ttutorial can be found by going to the Help menu in Minitab, selecting Tutorials then selecting 2-Sample t.
Read through Uses, Data and How To in the Tutorial window.
Note: The data files referenced in the tutorial are available in DocSharingfile (Minitab_Sample DataSets_HelpMenu). I suggest you print out the steps needed to perform the deliverables for the lab and as these items/steps come up in the tutorials, also use the HealthCareData.mpj data set to work along at that point.
For a specific example, choose Stat, Basic Statistics and then 2-Sample t. In the dialog box that pops ups, select Help.
You will want to do the same with the Paired-t in both the Tutorial (Help, Tutorial) and the Help in the Paired-t itself (Stat, Basic Statistics, Paired-t).
Independent Samples t-Test
1. Open the HealthCareData.mpj file using Minitab.
2. Will the rectangular nature of the Minitab data set require us to create a new data file for this analysis due to all the missing values at the end of Second_BDI and BDI_treatment? If you are not sure, try it both ways, observe any differences, then take the appropriate action and continue to step 3.
3. From Menus, select Stat,Basic Statistics and then 2-Sample t.
4. Select Second_BDI for the Samples and BDI_treatment for the Subscripts. Make sure to select Assumeequal variances.
5. Click OK to perform the t-Test and view the results in the output window. Review the results. This is the point at which you perform a contextual analysis of the output.
6. Think about it: Were all the assumptions for a t-Test with independent samples met? What did the t-Test show? Are the results significant? What conclusions would you draw?
Paired-Sample T-Test
1. If necessary open the HealthCareData.mpj file using Minitab.
2. Will the rectangular nature of the Minitab data set require us to create a new data file for this analysis due to all the missing values at the end of Second_BDI and BDI_treatment? If you are not sure, try it both ways, observe any differences, then take the appropriate actions and continue to step 3.
3. From Menus, select Stat,Basic Statistics and then Paired-t.
4. Select two variables: Diab_Pretest andDiab_Posttest.
Click OK then review the results. This is where you begin the contextual analysis.
5. Think about it: Patients need to score 95% or better to be discharged. Was the teaching program effective? While the test may have indicated the means of the two groups were indeed significantly different, is this all the hospital needs to assess their teaching effectiveness? What other follow up analysis would you recommend?
Attachment:- Instructions.rar