Scenario 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 | Homework #1 Solution - Grade One Essays

Scenario 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 | Homework #1 Solution

Competency

In this project, you will demonstrate your mastery of the following competency:

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  • Apply statistical techniques to address research problems
Scenario
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.

Reference

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

Directions

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: You are a data analyst for a basketball team
    • 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.
  2. 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: You are a data analyst for a basketball team
    • 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.
    • Get Total Compensation Plan Help!! You are a data analyst for a basketball team
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. You are a data analyst for a basketball team. Review the file to make sure that every step and all your outputs are included. Submit the HTML file as part of your submission.

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.

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