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 (whi
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,…).
- Develop an equation to model the data using a regression analysis approach and explain your calculation process in Excel.
- Calculate the r-square statistic using Excel. Interpret the meaning of the r-square statistic in this case.
- Determine three conclusions that address the initial observations and are supported by the regression analysis.
CHART IS LISTED AS CHART 1
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):
- Develop an equation to model the data using a regression analysis approach and explain your calculation process, using Excel.
- 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.
- Determine three conclusions based on the correlation of the number of lesions to minutes of sunlight exposure, using regression analysis.
CHART IS ATTACHED
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).
- State the null hypothesis and the alternative hypothesis for this situation.
- 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.
- Determine three conclusions on the effectiveness of the medication by addressing observations or hypotheses regarding these initial tests.
CHART IS ATTACHED
PLEASE LOOK AT POWERPOINT AND FOLLOW THOSE DIRECTIONS
Strayer University
Mathematical Methods for Health Services
MAT 543
Review of Case Study – Week 5
PLEASE put your phone / computer on MUTE
Call will start promptly at 8:00 PM ET and will be recorded
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Case Studies 1/2
Case Study 1: Statistical forecasting is necessary related a possible 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. The key researcher has identified possible statistically valid correlations.
Case Study 2: The director of the health center clinic at East-Southern KentuckyCommunity College (ESKCC) has seen the benefits of total quality management (TQM) and feels that it would help improve the operations at the ESKCC clinic. He has made some positive changes to the staffing of the clinic, but now feels that he must tackle making improvements to its operations. Consequently, he has created a TQM team (of which you are a part) and has made certain that they have received the necessary training to start examining the various processes within the healthcenter's operations.
I will provide you with more detail guidance in an announcement for each Case Study
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Week 5 Assignment – Case Study: Statistical Forecasting
General Situation:
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.
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.
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Task 1: Case Study 1 – More Information
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.
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Task 1: Case Study 1 – 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,…).
Develop an equation to model the data using a regression analysis approach and explain your calculation process in Excel.
Calculate the r-square statistic using Excel. Interpret the meaning of the r-square statistic in this case.
Determine three conclusions that address the initial observations and are supported by the regression analysis.
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Task 1: Case Study 1 – How do I approach this?
LEARN – Learn item options
Readings
Click the activity title, zyBooks – Week 5: Multiple Regression, to access the reading from Quantitative Methods for Health Services.
Multimedia
Watch the following video to learn more about using Excel for analysis.
Excel Data Analysis: Forecasting – Multiple Regressions (video collection) (36 min).
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Some Useful Videos for Your Use
Here are two youtube videos that are exceptionally useful
https://www.youtube.com/watch?v=WOJR0GP1fsU&t=46s – Linear Regression
https://www.youtube.com/watch?v=0oc49DyA3hU – Hypothesis testing
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Task 2: Case Study 1 – Information
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):
Develop an equation to model the data using a regression analysis approach and explain your calculation process, using Excel.
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 hours 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 hours.
Patient 10 – 219 hours.
Patient 11 – 84 hours.
Determine three conclusions based on the correlation of the number of lesions to hours of sunlight exposure, using regression analysis.
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Task 2: Case Study 1 – How do I approach it?
LEARN – Learn item options
Readings
Click the activity title, zyBooks – Week 5: Multiple Regression, to access the reading from Quantitative Methods for Health Services.
Multimedia
Watch the following video to learn more about using Excel for analysis.
Excel Data Analysis: Forecasting – Multiple Regressions (video collection) (36 min).
Prediction of other data points – note that they must be in the range of your existing data.
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Task 3: Case Study 1 – Information
Effectiveness of Lotions:
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).
State the null hypothesis and the alternative hypothesis for this situation.
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.
Determine three conclusions on the effectiveness of the medication by addressing observations or hypotheses regarding these initial tests.
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Task 3: Case Study 1 – How do I approach it?
LEARN – Learn item options
Readings
Click the activity title, zyBooks – Week 5: Multiple Regression, to access the reading from Quantitative Methods for Health Services.
Multimedia
Watch the video included to learn more about using Excel for analysis.
Excel Data Analysis: Forecasting – Multiple Regressions (video collection) (36 min).
Use Anova to compare three different sets of results
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Task 4: Case Study 1 – Final Requirements
Now that you have your data analysis complete
Provide a three-paragraph summary of the findings you learned through the analysis.
Provide three data-driven suggestions for further exploration.
Please Note:
Not looking for pages of writing – but rather calculations using linear regression techniques
Not looking for lots of references – but please more than what is required.
Not looking for lots of explanation
Just simple calculations – and a thorough explanation of the method that you used and why
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Some Useful Videos for Your Use
Here are two youtube videos that are exceptionally useful
https://www.youtube.com/watch?v=WOJR0GP1fsU&t=46s – Linear Regression
https://www.goskills.com/Lean-Six-Sigma/Resources/Use-anova-in-Excel – Anova – step by step – must read this, not a video
https://www.youtube.com/watch?v=0NwA9xxxtHw – ANOVA explanation
Here are several youtube videos that you might find helpful in addition to the videos that are in the course. These are strictly focused on linear regression – where there are just two variables involved (an independent variable for the x-axis and a dependent variable for the y-axis.
https://www.youtube.com/watch?v=L_a8Z0BVjyM
https://www.youtube.com/watch?v=KwQsV77bYDY (shows the long way to do the calculations)
https://www.youtube.com/watch?v=9wX1a1J4WOI
Add Data Analysis Pack into Excel: https://www.youtube.com/watch?v=_yNxLFagKgw
You can also search the Khan Academy for information on help as well.
I expect you to do all calculations in Excel.
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Steps to Prevent Appearance of AI Violations
Make certain that you cite all materials taken from external references.
Nothing wrong if you cite these materials correctly
Look through Dr. Seuss’ Green Eggs and Ham presentation (posted in Week 1)
Do not restate the problem in your homework
No need to do this on your answer sheet
Results in an increased score on SafeAssign analysis of your submissions
I examine closely any submission with a SafeAssign score of 40% or higher
May instruct student to redo
May report student to Strayer administration with AI issue being cited on school records.
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