Assignment: Project 4 Inferences for Difference in Two Population Means

Math 13 - Perez Sandbox
2026-01-18T05:16:21Z

Due:

Module 25.3 Unit 9 Project

Use the following dataset for insurance claims to complete the project for difference in two population means

Insurance.csv

Overview: This project is different from others. Instead of working in groups, we will start with individual work using the Art of Stat web app, followed by a short discussion, and then you will have a short amount of time to revise your work. We will repeat this cycle 3 times with 3 separate problems. Your instructor may require you to turn in a written report.

Instructions:

1. Download the following dataset insurance.csv

2. Log into ArtofStat.com, and navigate the Confidence Intervals & Tests Comparing Two Groups Applications. Click on Compare Two Means Application.

3. Choose upload the CSV file into the Enter Data Field

4. Select Browse and Upload insurance.csv into the Choose CSV File field

You should see an Uploaded dataset with headings of AGE, SEX, BMI, CHILDREN, SMOKER, REGION and CHARGES – You will use this dataset to answer all 3 problems.

5. Select a Group Variable to describe the Populations to Analyze (you can only choose a variable with two options two have two distinct populations, ie SEX or SMOKER – If you want to separate the data by other variables, see below) *

6. Open a Word document. Your instructor will project a problem onto the overhead screen. Type the research question into your Word document.

7. Write a conclusion about the Insurance claims and answers to the research question.

Warm-Up: We will do a quick warm up before we get started.

1. Suppose your classmate collected a different random sample of the same size to conduct this study. When you discuss your work, which of the following should be the same?

ArtofStat Procedure Sample Mean P-Value

Hypothesis Standard Error Lower and Upper Limits of Confidence Interval

Degrees of Freedom T-Statistic Conclusion

2. Do smokers have less children than non-smokers?

Your classmate says reject the Ho in favor of Ha. What feedback do you have for him?

The Three Problems

1. Are females individual medical costs billed by health insurance less than they are for males in this study?

2. Are smokers individual medical costs billed by health insurance greater than non-smokers?

3. Is there a difference in BMI for males and females?

About Dataset

Context

Machine Learning with R by Brett Lantz is a book that provides an introduction to machine learning using R. As far as I can tell, Packt Publishing does not make its datasets available online unless you buy the book and create a user account which can be a problem if you are checking the book out from the library or borrowing the book from a friend. All of these datasets are in the public domain but simply needed some cleaning up and recoding to match the format in the book.

Content

Columns

age: age of primary beneficiary

sex: insurance contractor gender, female, male

bmi: Body mass index, providing an understanding of body, weights that are relatively high or low relative to height,
objective index of body weight (kg / m ^ 2) using the ratio of height to weight, ideally 18.5 to 24.9

children: Number of children covered by health insurance / Number of dependents

smoker: Smoking

region: the beneficiary's residential area in the US, northeast, southeast, southwest, northwest.

charges: Individual medical costs billed by health insurance

Acknowledgements

The dataset is available on GitHub here.

Inspiration

Can you accurately predict insurance costs?

Module 25.3 Unit 9 Project

Use the following dataset for insurance claims to complete the project for difference in two population means

Insurance.csv

Overview: This project is different from others. Instead of working in groups, we will start with individual work using the Art of Stat web app, followed by a short discussion, and then you will have a short amount of time to revise your work. We will repeat this cycle 3 times with 3 separate problems. Your instructor may require you to turn in a written report.

Instructions:

1. Download the following dataset insurance.csv

2. Log into ArtofStat.com, and navigate the Confidence Intervals & Tests Comparing Two Groups Applications. Click on Compare Two Means Application.

3. Choose upload the CSV file into the Enter Data Field

4. Select Browse and Upload insurance.csv into the Choose CSV File field

You should see an Uploaded dataset with headings of AGE, SEX, BMI, CHILDREN, SMOKER, REGION and CHARGES – You will use this dataset to answer all 3 problems.

5. Select a Group Variable to describe the Populations to Analyze (you can only choose a variable with two options two have two distinct populations, ie SEX or SMOKER – If you want to separate the data by other variables, see below) *

6. Open a Word document. Your instructor will project a problem onto the overhead screen. Type the research question into your Word document.

7. Write a conclusion about the Insurance claims and answers to the research question.

Warm-Up: We will do a quick warm up before we get started.

1. Suppose your classmate collected a different random sample of the same size to conduct this study. When you discuss your work, which of the following should be the same?

ArtofStat Procedure Sample Mean P-Value

Hypothesis Standard Error Lower and Upper Limits of Confidence Interval

Degrees of Freedom T-Statistic Conclusion

2. Do smokers have less children than non-smokers?

Your classmate says reject the Ho in favor of Ha. What feedback do you have for him?

The Three Problems

1. Are females individual medical costs billed by health insurance less than they are for males in this study?

2. Are smokers individual medical costs billed by health insurance greater than non-smokers?

3. Is there a difference in BMI for males and females?

About Dataset

Context

Machine Learning with R by Brett Lantz is a book that provides an introduction to machine learning using R. As far as I can tell, Packt Publishing does not make its datasets available online unless you buy the book and create a user account which can be a problem if you are checking the book out from the library or borrowing the book from a friend. All of these datasets are in the public domain but simply needed some cleaning up and recoding to match the format in the book.

Content

Columns

age: age of primary beneficiary

sex: insurance contractor gender, female, male

bmi: Body mass index, providing an understanding of body, weights that are relatively high or low relative to height,
objective index of body weight (kg / m ^ 2) using the ratio of height to weight, ideally 18.5 to 24.9

children: Number of children covered by health insurance / Number of dependents

smoker: Smoking

region: the beneficiary's residential area in the US, northeast, southeast, southwest, northwest.

charges: Individual medical costs billed by health insurance

Acknowledgements

The dataset is available on GitHub here.

Inspiration

Can you accurately predict insurance costs?