MAT 210 SU Week 4 Foundation of Data Driven Decisions Questions
Problem Solving – Data Analysis (Mathematical Reasoning)
You’ll practice your problem solving skill by identifying foundational statistical concepts and explaining how data-driven decision making can help inform real world problems. This will provide you with a solid foundation that will help you to not only be successful in this course, but to learn to make smarter, data-driven decisions in your personal and professional life.
Practice your problem solving skill by answering questions about statistical concepts and the benefits and uses of data-driven decision making.
Steps to Complete:
STEP 1: Answer the questions below in a Word document.
STEP 2: Save and submit your Word document in the Assignment link in the Week 3 Submit page in BlackBoard.
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.
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:
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:
5. How does analyzing data on these real-world problems aid in problem-solving and drawing conclusions? Be sure to note the value and benefits of data-driven decision-making.