Academic paper on MAT210 – Data-Driven Decision Making covering descriptive and inferential statistics with real-world examples. The assignment explains how descriptive statistics summarize sample data and inferential methods generalize findings to populations. Includes examples on sleep patterns, diet, wellness, study habits, and physical activity. Useful for students needing help with assignments, homework assistance, research papers, or reviews of articles in statistics and data analysis.

MAT210 – Data-Driven Decision Making: Descriptive vs Inferential Statistics

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.

According to Frost’s (2018) research, descriptive statistics summarize and display the data for a particular sample to better comprehend observations. For instance, data on the scores would be gathered and examined to determine how a particular class has performed. On the other hand, inferential statistics uses data from a sample to conclude the greater population from which the sample was obtained (Frost, 2018). For instance, information might be randomly gathered from various institutions and examined to see how students in a particular grade have performed across the nation.

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?

The null hypothesis on the issue would be that eating right before bed does not influence sleep patterns. The alternative hypothesis, on the other hand, would be that eating right before going to bed influences sleep patterns.

What type of data will you be looking for?

Quantitative data would be ideal for this study. Data on the individuals’ sleep quality would be needed for the study. The information may include the number of hours each person slept and the duration between eating and going to bed.

What methods would you use to gather information? How would the results of the data influence decisions you might make about eating and sleeping?

A questionnaire would be an essential instrument in the research, wherein the respondents would be asked to provide information on a range of sleep-related practices. A critical tool for assessing sleep quality is the PSQI (Pittsburgh Quality Sleep Index) (Pacheco & Rehman, 2022). The results of the PSQI will identify any anomalies in sleep patterns that may be causing the subjects’ general poor sleep quality by providing facts about their sleeping patterns. The study’s findings can assist explain how various sleeping habits might be understood via feeding strategies. For instance, I would consider adjusting my eating time to earlier before bed to get good quality sleep.

Need help understanding topics like descriptive and inferential statistics, hypothesis testing, or data-driven decision-making? At My Homework Helpline, we provide step-by-step support for academic assignments, homework, and real-world statistical problems. Whether you’re working on research design, analyzing data, or preparing your assignment, our tutors make the process simple and clear. Get expert statistics homework assistance today and improve your confidence in solving problems using reliable data analysis.

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?

We would need to confirm that the methodology utilized has been thoroughly vetted and is based on current research to assess the validity of the findings in this study. The participants should also be sufficient, well-defined, and representative of the total population. On the other hand, statistical tools can be employed to determine the data’s dependability. The test-retest reliability is one of the quantitative metrics that can be used to assess dependability. To determine whether or not results are accurate, we must also be aware of potential biases and errors.

What questions would you ask to find out more about the quality of the data?

Questions that can be asked include what are the study’s assumptions, constants, and variables? Do the participants, for instance, work out concurrently to enhance their wellness or have similar economic statuses? It’s crucial to consider aspects like these to link consuming green tea to improved happiness and well-being accurately. In addition, knowledge of how the samples were selected would be significant—precisely, sample size, procedure, and type of sampling.

Why is it important to gather and report valid and reliable data?

Gathering and reporting valid and reliable data is essential in statistics since a sample’s attributes and features are used to generalize about the entire population.

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 to help support your response:

Example 1: As a researcher, I want to determine whether physical activity influences an individual’s health. To conduct the study, I would issue out physical activity records or logs to random individuals across the nation for participants to provide detailed information on physical activities during the day. I would then collect data on those that engage in physical activities and those that do not, the hours spent in those activities, and their health status, for instance, the presence of any underlying illnesses. Next, I would apply the one-way Anova test to analyze the variance between male and female individuals.

Example 2: As a student, I’m curious to know if studying before bed affects test results when studying for examinations. To determine whether or not they sleep before studying, I would ask random students in my class and then match the data with the corresponding scores. Because there are two categories to be compared in this instance that is made up of various subjects, I would use an independent t-test to see if exam results substantially increase when a student gets some sleep before studying.

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.

Since it ensures validity and reliability of the associations or interactions of the elements in the surrounding circumstances, data analysis of real-world problems is vital (Vidjikant, 2022). As a result, the inaccuracies in the findings are reduced with the proper scientific approach and awareness of the hypotheses, constants, and variables. The suitable proposals following research may then be made to ensure the best outcomes and conclusions further.

References

Frost, J. (2018). Difference between descriptive and inferential statistics. Statistics by Jim. Retrieved July 21, 2022, from https://statisticsbyjim.com/basics/descriptive-inferential-statistics/

Pacheco, D., & Rehman, A. (2022, April 14). How is sleep quality calculated? Sleep Foundation. Retrieved July 22, 2022, from https://www.sleepfoundation.org/sleep-hygiene/how-is-sleep-quality-calculated

Vidjikant, S. (2022, June 20). Data-Driven decision-making. Softjourn. Retrieved July 21, 2022, from https://softjourn.com/insights/data-driven-decision-making