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APA
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Mathematics & Economics
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Coursework
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English (U.S.)
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Topic:

Validating Data and The Difference between Descriptive and Inferential Statistical Methods

Coursework Instructions:

1. Explain the difference between descriptive and inferential statistical methods and give examples of how each could help you draw a conclusion in the real world. 2. List each step you would take to conduct a statistical study on this topic and explain what you would do to complete each step. 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 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 analyse each problem. 5. How does analysing data on these real world problems aid in problem solving and drawing conclusions?

Coursework Sample Content Preview:

Statistical Methods
Student’s Name
Institutional Affiliation
Course
Instructor
Data
Statistical Methods
Question 1.
Descriptive statistical methods provide population descriptions using data either through tables, graphs, or numerical calculations, for instance, descriptions of the production of agricultural products in a certain period. Inferential statistical methods make predictions and inferences about a population using a sample taken from the population, for instance, causes of miscarriage among women aged 25-35 years (Amrhein et al., 2019).
Question 2.
steps used in conducting a statistical study include;
1 Data collection, where relevant and appropriate data collection methods are used to collect data on sleeping patterns.
2 The next step is data organization, where the collected data is arranged in order of their relationship.
3 The next step is data presentation, where the organized data is presented in either table, graphs, charts, and so forth.
4 The next step is the analysis, where different programs are used to analyze the data presented.
5 The last step is an interpretation of data where the meaning of the data is drawn.
The hypothesis for the issue is that eating before bed negatively influences the sleeping patterns of healthy individuals.
The type of data that may be collected about this issue is a quantitative type of data where people will give their experience on the sleep patterns after meals before going to bed.
The most appropriate methods to gather information on the influence of eating before bed on sleep patterns are open-ended questions and personal interviews.

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