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MAT 243 Southern New Hampshire University Statistical Analysis Projects Report

MAT 243 Southern New Hampshire University Statistical Analysis Projects Report

Question Description

Use the link in the Jupyter Notebook activity to access your Python script. Once you have made your calculations, complete this discussion. The script will output answers to the questions given below. You must attach your Python script output as an HTML file and respond to the questions below.

In this discussion, you will apply the statistical concepts and techniques covered in this week’s reading to calculate a confidence interval and perform hypothesis testing for a manufacturing process.

The manufacturing process at a factory produces ball bearings that are sold to automotive manufacturers. The factory wants to estimate the average diameter of a ball bearing that is in demand to ensure that it is manufactured within the specifications. Suppose they plan to collect a sample of 50 ball bearings and measure their diameters to construct a 90% and 99% confidence interval for the average diameter of ball bearings produced from this manufacturing process.

The sample of size 50 was generated using Python’s numpy module. This data set will be unique to you, and therefore your answers will be unique as well. Run Step 1 in the Python script to generate your unique sample data. Check to make sure your sample data is shown in your attachment.

In your initial post, address the following items. Be sure to answer the questions about both confidence intervals and hypothesis testing.

  1. In the Python script, you calculated the sample data to construct a 90% and 99% confidence interval for the average diameter of ball bearings produced from this manufacturing process. These confidence intervals were created using the Normal distribution based on the assumption that the population standard deviation is known and the sample size is sufficiently large. Report these confidence intervals rounded to two decimal places. See Step 2 in the Python script.
  2. Interpret both confidence intervals. Make sure to be detailed and precise in your interpretation.

It has been claimed from previous studies that the average diameter of ball bearings from this manufacturing process is 2.30 cm. Based on the sample of 50 that you collected, is there evidence to suggest that the average diameter is greater than 2.30 cm? Perform a hypothesis test for the population mean at alpha = 0.01.

In your initial post, address the following items:

  1. Define the null and alternative hypothesis for this test in mathematical terms and in words.
  2. Report the level of significance.
  3. Include the test statistic and the P-value. See Step 3 in the Python script. (Note that Python methods return two tailed P-values. You must report the correct P-value based on the alternative hypothesis.)
  4. Provide your conclusion and interpretation of the results. Should the null hypothesis be rejected? Why or why not?

In your follow-up posts to other students, review your peers’ calculations and provide some analysis and interpretation:

  1. How do their confidence intervals compare with yours?
  2. If the population standard deviation is unknown and the sample size is not sufficiently large, would you still use the Normal distribution to calculate these confidence intervals, or would you choose another distribution? If the latter, which distribution would you choose?

Remember to attach your Python output and respond to all questions in your initial and follow-up posts. Be sure to clearly communicate your ideas using appropriate terminology. Finally, be sure to review the Discussion Rubric to understand how you will be graded on this assignment.

PART 2 :


You are a data analyst for a basketball team. You have found a large set of historical data, and are working to analyze and find patterns in the data set. The coach of the team and your management have requested that you use descriptive statistics and data visualization techniques to study distributions of key variables associated with the performance of different teams. Data-driven analytics will help the management make decisions to further improve your team’s performance. You will use the Python programming language to perform your statistical analysis. You will also need to present a report of your findings to the team’s management. Since the managers are not data analysts, you will need to interpret your findings and describe their practical implications. The managers will use your report to find areas where the team can improve its performance.

Note: This data set has been “cleaned” for the purposes of this assignment.


FiveThirtyEight. (April 26, 2019). FiveThirtyEight NBA Elo dataset. Kaggle. Retrieved from https://www.kaggle.com/fivethirtyeight/fivethirtye…


For this project, you will submit the Python script you used to make your calculations and a summary report explaining your findings.

  1. Python Script: To complete the tasks listed below, open the Project One Jupyter Notebook link in the Assignment Information module. Your project contains the NBA data set and a Jupyter Notebook with your Python scripts. In the notebook, you will find step-by-step instructions and code blocks that will help you complete the following tasks:
    • Choose and create a data visualization.
    • Calculate descriptive statistics including mean, median, min, max, variance, and standard deviation.
    • Construct confidence intervals for a population proportion and a population mean.
  1. Summary Report: Once you have completed all the steps in your Python script, you will create a summary report to present your findings. Use the provided template to create your report. You must complete each of the following sections:
    • Introduction: Set the context for your scenario and the analyses you will be performing.
    • Data Visualization: Identify and interpret your chosen data visualization.
    • Descriptive Statistics: Identify and interpret measures of central tendency and variability.
    • Confidence Intervals: Identify and interpret the lower and upper limits of confidence intervals.
    • Conclusion: Summarize your findings and explain their practical implications.

What to Submit

To complete this project, you must submit the following:

Python Script
Your Jupyter Notebook Python script contains all the statistical analyses you completed for this project. You downloaded your work as an HTML file. Review the file to make sure that every step and all your outputs are included. Submit the HTML file as part of your submission. Review the Jupyter Notebook in Codio Tutorial in the Supporting Materials section if you need help.

Summary Report
Use the provided template to create your summary report. The template contains guiding questions to help you complete each section. Be sure to remove these questions before submitting your report. Your summary report should be submitted as a 3- to 5-page Microsoft Word document. It should include an APA-style cover page and APA citations for any sources used. Use double spacing, 12-point Times New Roman font, and one-inch margins.

Supporting Materials

The following resource(s) may help support your work on the project:

Document: Jupyter Notebook in Codio Tutorial
This tutorial will help you become familiar with the Jupyter Notebook interface. You will learn how to open, complete, save, and download your Jupyter Notebook for this project.

Shapiro Library: APA Style Guide
This guide will help you format your cover page and references according to APA style. You are not required to use external resources for this project. However, if you do use any resources, you must cite them in APA format.

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