MAT 210 Strayer University Problem Solving Data Analysis Worksheet
- June 26, 2022/ Uncategorized
Course: MAT210 – Data-Driven Decision Making
Skill(s) Being Assessed: Problem Solving – Data Analysis (Mathematical Reasoning)
What to Submit / Deliverables: Word Document
Steps to Complete:
STEP 1: Answer the questions below in a Word document.
1. Explain the difference between descriptive and inferential statistical methods and give an example of how each could help you draw a conclusion in the real world.
2. You would like to determine whether eating before bed influences sleep patterns. List each step you would take to conduct a statistical study on this topic and explain what you would do to complete each step. Then, answer the questions below.
- What is your hypothesis on this issue?
- What type of data will you be looking for?
- What methods would you use to gather information?
- How would the results of the data influence decisions you might make about eating and sleeping?
3. A company that sells tea and coffee claims that drinking two cups of green tea daily has been shown to increase mood and well-being. This claim is based on surveys asking customers to rate their mood on a scale of 1–10 after days they drink/do not drink different types of tea. Based on this information, answer the following questions:
- How would we know if this data is valid and reliable?
- What questions would you ask to find out more about the quality of the data?
- Why is it important to gather and report valid and reliable data?
4. Identify two examples of real-world problems that you have observed in your personal, academic, or professional life that could benefit from data driven solutions. Explain how you would use data/statistics and the steps you would take to analyze each problem. You may also choose topics below (or examples from the weekly content) to help support your response:
- Productivity at work.
- Financial decisions and budgeting.
- Health and nutrition.
- Political campaigns.
- Quality testing in products.
- Human resource policies.
- Algorithms for programming/coding.
- Accounting & financial policies.
- Crime reduction and trends.
- Environmental protection / Emergency preparedness.