Module Five Problem Set

Overview

In each module, you will be learning about different statistical functions in R. You will apply these functions to specific data sets, creating models that can be used to understand and solve real-world problems. You will gain practice creating a model, reporting and interpreting its statistics, evaluating its significance, and using it to make predictions.

Note: Begin working on the readings and the problem set early each week. This will help make sure that you are prepared for the weekly discussion.

Prompt

In this activity, you will explore a logistic regression model that has been created for you. Then you will be asked to create your own logistic regression models, and write a mini-report based on your findings.

1. Access the R scripts for this problem set by using the Jupyter Notebook link in Module Five. In your Jupyter Notebook, you have been given a set of steps that explains how to create a logistic regression model. Go through each step, examining the scripts and their output. If you are not sure how a specific script works or how to understand the output of a script, review the readings. Reach out to your instructor if you need additional help.

2. Review the  Module Five Problem Set Report template  to understand the questions that you will need to answer for this assignment. Then, write your own scripts to create the logistic regression models described in the report. Refer to the scripts that you were given as examples to guide your work.

3. Use the outputs of your scripts to answer all of the questions in your problem set report. The report has been divided into several sections. Each section contains questions to guide your analysis. Be sure to fully answer all of the questions and complete the following sections:

· Introduction: Communicate all ideas by presenting the context of your analyses.

· Reporting Results: Report the results of the model by listing and interpreting various model statistics.

· Evaluating Model Significance: Evaluate the significance of the model by reporting parameter estimates and performing hypothesis testing for each estimate and the overall model.

· Making Predictions Using the Model: Make predictions based on the model by reporting prediction values.

· Conclusion: Communicate all ideas by summarizing and interpreting the practical implications of the results.

Guidelines for Submission

You will submit your completed problem set report as a Word document. Use 11-point Calibri font and one-inch margins. You must use the equation editor where appropriate.

You will also submit the HTML file containing the outputs of your R scripts from the Jupyter Notebook.