Quantitative research case study | MAT543 | Strayer University

Week 5 Assignment – Case Study: Statistical Forecasting

Dr. Megan Zobb, a key researcher within the North Luna University  Medical Center, has been studying a new variant of a skin disease virus  that seems to be surfacing among the North Luna University population.  This variant (which has been tentatively named Painful Rash or PR),  leads to the formation of surface lesions on an individual’s body. These  lesions are very similar to small boils or isolated shingles sores.  These PR lesions are not necessarily clustered as shingles lesions are,  but are isolated across the body.

Insights From Initial Interviews

Megan is initiating some efforts at a preliminary analysis. She  has seen 20 initial patients and made several observations about the  skin disease. She wants to analyze this initial data before structuring  and recommending a more encompassing study.

The signs and symptoms of this disorder usually affect multiple  sections of the patient’s body. These signs and symptoms may include:

  • Pain, burning, numbness or tingling, but pain is always present.
  • Sensitivity to touch.
  • A red rash that begins a few days after the pain.
  • Fluid-filled blisters that break open and crust over.
  • Itching.

 Some people also experience:

  • Fever.
  • Headache.
  • Sensitivity to light.
  • Fatigue.


Pain is always the first symptom of PR. For some, it can be intense.  Depending on the location of the pain, it can sometimes be mistaken for a  symptom of problems affecting the heart, lungs, or kidneys. Some people  experience PR pain without ever developing the rash. The degree of pain  that the individual experiences is seemingly proportional to the number  of lesions.

Dr. Zobb is extremely concerned that this new variant is  especially challenging to the younger population, who are active and  like to be outdoors. She has asked you as an analyst and statistician  for some assistance in analyzing her initial data. She is not a  biostatistician, so she requests that you explain the process you use  and your interpretation of the results for each task.

Initial Data Analysis

Dr. Zobb has accumulated some data on an initial set of 20  patients across multiple age groups. She believes that the data suggests  younger individuals are affected more than others. She wants you to  complete the tasks shown here based on the data below.

For each of the following, provide a detailed explanation of the  process you used along with your interpretation of the results. Submit  the response in a Word document and attach your Excel spreadsheet to  show your calculations (where applicable). Be sure to number each  response (e.g., 1.a, 1.b,…).

  1. Develop an equation to model the data using a regression analysis approach and explain your calculation process in Excel.
  2. Calculate the r-square statistic using Excel.  Interpret the meaning of the r-square statistic in this case.  
  3. Determine three conclusions that address the initial observations and are supported by the regression analysis.

( Screenshot one- Regression Analysis initial data)


Effects of Sunlight Analysis

In her initial observations, Dr. Zobb notices that the number of  lesions that appear on a patient seems to be dependent on the amount of  direct sunlight exposure that the patient receives. She is uncertain at  this point why this would be the case, but she is a good experimentalist  and is trying to establish some observations that have statistical  validity. She has taken a limited amount of data on 8 patients and wants  you to complete the appropriate analysis based on the data below (be  sure to show your work):

  1. Develop an equation to model the data using a regression analysis approach and explain your calculation process, using Excel.  
  2. Megan has a small group of three additional patients that are  the same age that she wants to examine for lesions.  She knows the  number of minutes of continuous exposure to direct sunlight that each  has experienced. Predict the number of lesions that each of these  patients will have based on the regression analysis that you completed  in your initial data analysis:        
    • Patient 9 – 193 minutes.
    • Patient 10 – 219 minutes.
    • Patient 11 – 84 minutes

3.  Determine three conclusions based on the correlation of the  number of lesions to minutes of sunlight    exposure, using regression  analysis. 

(Screenshot 2 Sunlight exposure regression data)


Over the Counter Medication Effectiveness Analysis

Dr. Zobb wants to test several over the counter lotions—that is,  lotions available without a prescription—that can be applied directly to  the lesions. She wants to determine whether there is a difference in  the mean length of time it takes these three types of pain lotions to  provide relief from the pain caused by these lesions. Megan is hoping  that one of these lotions might be more promising than the others.  Several sufferers (with roughly the same number of lesions) are randomly  selected and given one of the three medications. Each sufferer records  the time (in minutes) it takes the medication to begin working. The  results are shown in the table below. She asks you to answer these  questions (be sure to show your work).

  1. State the null hypothesis and the alternative hypothesis for this situation.
  2. At α = 0.01, can you conclude that the mean times are  different? Assume that each population of relief times is normally  distributed and that the population variances are equal.  Hint: Use  a one-way ANOVA to solve this problem. Be certain to show your  calculations and describe the process you used to solve this problem.
  3. Determine three conclusions on the effectiveness of the  medication by addressing observations or hypotheses regarding these  initial tests.

(Screenshot three-  Effectiveness of Over the Counter Medications )

 Summary of Data Analysis
Now that you have all of your data analysis:

  1. Provide a three-paragraph summary of the findings you learned through the analysis.
  2. Provide three data-driven suggestions for further exploration.
  3. This course requires the use of Strayer Writing Standards. For  assistance and information, please refer to the Strayer Writing  Standards link in the left-hand menu of your course. Check with your  professor for any additional instructions.
    The specific course learning outcome associated with this assignment is:
  • Recommend a course of action utilizing quantitative methods for  health services including biostatistics, forecasting, and the modeling  of predictive functions.
  • By submitting this paper, you agree: (1) that you are  submitting your paper to be used and stored as part of the SafeAssign™  services in accordance with the Blackboard Privacy Policy;  (2) that your institution may use your paper in accordance with your  institution’s policies; and (3) that your use of SafeAssign will be  without recourse against Blackboard Inc. and its affiliates.  

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