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MATH325 Lab 3 Using Microsoft Excel Statistics to calculate the various T-Tests The steps required for completing the deliverables for this assignment, including screen shots that c

Jamez

• 5 min read

 MATH325 Lab 3

Using Microsoft Excel Statistics to calculate the various T-Tests

The steps required for completing the deliverables for this assignment, including screen shots that correspond to these instructions, are outlined below. Complete the questions below and paste the answers from Excel below each question (type your answers to the questions where noted). Therefore, your response to the lab will be this ONE submitted document.

Context: Remember that statistics are far more than numbers or values – you need to know the context to perform a good analysis!

  1. 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.

  1. Paired Sample T-Test:  Assess the effectiveness of the hospital’s diabetic education program by comparing pre-teaching and post-teaching 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).

 


 

Review the Microsoft Excel information on T-Tests: https://support.microsoft.com/en-us/office/use-the-analysis-toolpak-to-perform-complex-data-analysis-6c67ccf0-f4a9-487c-8dec-bdb5a2cefab6

Scroll down to t-Test, and click to expand:

Review the entire write-up on the Two-Sample t-Test:

  1. Independent Samples t-Test: The Independent Samples t-Test procedure compares means for two groups of cases. Ideally, for this test, the subjects should be randomly assigned to two groups, so that any difference in response is due to the treatment (or lack of treatment) and not to other factors. Example. Patients with high blood pressure are randomly assigned to a placebo group and a treatment group. The placebo subjects receive an inactive pill, and the treatment subjects receive a new drug that is expected to lower blood pressure. After the subjects are treated for two months, the 2-Sample t-Test is used to compare the average blood pressures for the placebo group and the treatment group. Each patient is measured once and belongs to one group. 

Note:  Patients with high blood pressure are not normally left untreated – this is an ethical question that arises all the time in healthcare studies. Could one ethically conduct such a study? Would such a study receive approval from the administration and medical boards? What legal issues would need to be addressed?

The Independent Samples t-Test is appropriate whenever two means drawn from independent samples are to be compared. The variable used to form the groups may already exist; however, a cut point on a continuous variable can be provided to dynamically create the groups during the analysis. As with all t-Tests, the Independent Samples t-Test assumes that each sample mean comes from a population that is reasonably normally distributed, especially with respect to skewness. Test variables with extreme or outlying values should be carefully checked; boxplots can be used for this.

 

  1. Open the HealthCareData.xlsx file using Microsoft Excel.
  2. Add a new worksheet into your workbook. Copy and paste the following data into the new worksheet:
  • Original_BDI (Column C)
  • BDI_Treatment (Column D)
  • Second_BDI (Column E)
  1. Highlight the header names in those columns and from the Home tab, select Sort & Filter, and Filter.
  1. Click the arrow next to the BDI_Treatment header, and sort the column from A to Z. This alphabetizes the data and makes it easier to see which group was in the placebo trial, and which group was in the medication trial.
  1. We are first going to see if there is a difference in Original_BDI between those who have been put into the treatment group versus the placebo group. From Data Analysis menu, select t-Test: Two-Sample Assuming Equal Variances. Click OK.
  1. For Variable 1 Range, in the Original_BDI column, select those associated with the treatment trial. For Variable 2 Range, in the Original_BDI column, select those associated with the placebo.
  1. 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. 
  2. Copy and paste your results below. 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?  

 

 

  1. Now repeat the test with the following inputs: For Variable 1 Range, in the Second_BDI column, select those associated with the treatment trial. For Variable 2 Range, in the Second_BDI column, select those associated with the placebo.
  2. 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. 
  3. Copy and paste your results below. Think about it:  What did the t-Test show?  Are the results significant?  What conclusions would you draw about the effectiveness of treatment on depression?

 

 

  1. Paired-Sample T-Test
  2. If necessary open the HealthCareData.xlsx file using Microsoft Excel.
  3. From Data Analysis menu, select t-Test: Paired Two Sample for Means. Click OK.
  1. Input for Variable 1 should be: Diab_Pretest (the data in Column H);
     Input for Variable 2 should be: Diab_Posttest (the data in Column I).

Click OK then review the results.  This is where you begin the contextual analysis.

  1. Paste the resulting output table below. Then 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? 

 

 

  1. Deliverable: Save this document and submit it into the Assignments, Week 4: Lab.

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