Week 5 Discussion

Hypothesis Testing: Chi-Square Test of Independence

A statistical hypothesis is a claim about a population parameter.Hypothesis testing is a way to build support for or against a population claim. There are many types of hypothesis tests. This week we will be using a Chi-Square Test of Independence to test the claim about the relationship between two categorical variables.

To prepare for this Discussion:

• Review the Week 5 Discussion resources.

Complete the MyLab Statistics homework and Week 5 Project before you work on the Discussion.

• Search for two strictly categorical variables. You cannot change a quantitative variable into a qualitative one by creating your own groups. Remember that you cannot use any of the variables that are used in this example or any previous discussion examples.
• Create a contingency table showing the results of your data collection.

Everyone will be testing to see if the two categorical variables you test are independent. You may have to search the internet or research your field of study for appropriate categorical variables. Stick to health-related topics. You cannot use rates, percentages or proportions in your contingency table. You must list counts.

Example:

A research report from the Working Group on Passive Smoking concluded that a link exists between passive smoking and prevalence of certain diseases.

Null hypothesis: Exposure to passive smoke and occurrence of common fatal

diseases are independent.

Alternative hypothesis: Exposure to passive smoke and occurrence of common fatal

diseases are dependent.

Contingency Table

Common Fatal Diseases

	Heart Disease	Cancer	Diabetes
Significant	185	145	95
None	56	63	44

Exposure to

Passive

Smoke

Significance level = .01

Degrees of freedom: 2

Test Statistic, X^2 = 4.1767

Critical X^2 = 5.991471

P-Value = 0.1239

By Day 5

Post a 2- to 3-paragraph write-up that includes the following:

1. Include your contingency table and describe the scenario you will be using for the hypothesis test. Give the null and alternative hypotheses and your level of significance.
2. Enter the counts for your qualitative variables into the Statdisk Sample Editor.
3. List the results of the hypothesis test.
4. Write a conclusion statement based on your comparison of the p-value and level of

significance. Your conclusion to accept or reject is always directed to the null

hypothesis.

1. List the degrees of freedom and how it was calculated.

Can someone please help me do this the topic could be on women's who breastfeed we can get the yes or no from there and how berastfeeding can help reduce cancer could be another variable or something else in the medical field.

Thank you!