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2.3 Statistics for Two Categorical Variables

4 min readdecember 29, 2022

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Additional Relative Frequencies

Lets look back at the from Unit 2.2.

https://firebasestorage.googleapis.com/v0/b/fiveable-92889.appspot.com/o/images%2FScreen%20Shot%202020-04-24%20at%204.45-FOqnu1Kcf68e.png?alt=media&token=f3628028-5fa2-4796-bcb8-db51f591a524

Courtesy of Starnes, Daren S. and Tabor, Josh. The Practice of Statistics—For the AP Exam, 5th Edition. Cengage Publishing.

We can find more than just joint relative frequencies here as there’s also marginal relative frequencies and conditional relative frequencies. 😲

Marginal Relative Frequency

A marginal relative frequency is the relative frequency of all the people in a certain category. For example, the marginal relative frequency of a "50-50 chance” is 1416/4826 as from the right margin, we see that 1416 overall respondents gave that response. In other words, the marginal relative frequencies are the row and column totals in a divided by the total for the entire table. ➕

Conditional Relative Frequency

On the other hand, the conditional relative frequency is the frequency that we have of a particular category given the fact that we know a subject is in another category. The category that we know is called the given, or , while the other is called the , just like independent and dependent variables on graphs.

For example, the conditional frequency for “50-50 chance given male” is 720/2459 because out of the 2459 males who responded, 720 of them said “50-50 chance.” When calculating a conditional relative frequency, our denominator (or total) is usually considerably smaller than that of overall total. 🧱

Determining Associations from a Two-Way Table

From a , we can use marginal and conditional relative frequencies to consider if two categorical variables are associated or not. To do this, see if two corresponding conditional relative frequencies across different categories are not the same. This is also the same as seeing if the conditional relative frequency is not the same as the marginal relative frequency for the . This makes it so that certain values are more likely to yield a certain result than others. That is, we can predict behavior given the fact that we know that an individual falls under a certain category. 💍

Example

Using the above, we can determine that the variables "gender" and "opinion" are independent, or not associated, because the marginal relative frequency of being "50-50 chance" is roughly equal to the conditional relative frequency of being "50-50 chance given male".

https://firebasestorage.googleapis.com/v0/b/fiveable-92889.appspot.com/o/images%2FScreen%20Shot%202020-04-24%20at%204.57-uj3PWu8h12Zr.png?alt=media&token=7eef3de2-ec3f-4451-9260-88f4ff6cb242

🎥Watch: AP Stats - Probability: Two Way Tables, Independence, Tree Diagrams, etc

Vocabulary Practice from 2.1 to 2.3 Material

Match the number with the letter that corresponds to its description! 😁

1. Two-way tables

2, Side-by-side bar graphs

3. Mosaic plots

4. Segmented bar graphs

5.

6.

7.

8. Marginal relative frequency

9. Conditional relative frequency

A. A graphical display that shows the relationship between two categorical variables by dividing the area of a rectangle into tiles that represent the different categories of both variables.

B. A graphical display that shows the distribution of a by displaying the frequency or relative frequency of each category as a bar.

C. A graphical display that shows the relationship between two categorical variables by dividing the bars in a bar graph into segments that represent the different categories of one of the variables.

D. A statistical table that shows the frequencies or relative frequencies of two categorical variables in a cross-tabulated format, with one variable represented by rows and the other by columns.

E. A variable that can take on a limited number of categories or values, such as "male" or "female," but cannot be meaningfully ordered or measured on a continuous scale.

F. A variable that can be measured or ordered on a continuous scale, such as height or weight.

G. The relative frequency of a particular category of a within another category, calculated by dividing the frequency or relative frequency of the first category within the second category by the total frequency or relative frequency of the second category.

H. The frequency or relative frequency of a particular category of a , calculated by dividing the frequency or relative frequency of that category by the total frequency or relative frequency for the entire sample or population.

I. A statistical concept that refers to the relationship between two variables, often used to describe the association between two categorical variables.

Answers

1. D

2. B

3. A

4. C

5. E

6. F

7. I

8. H

9. G

Key Terms to Review (6)

Bivariate Variable

: A bivariate variable is a type of variable that involves two variables and examines their relationship with each other. It explores how changes in one variable affect the other.

Categorical Variable

: A categorical variable is one that represents characteristics or qualities rather than numerical values. It consists of categories or groups into which data can be classified.

Dependent Category

: A dependent category refers to a variable or factor that is influenced by other variables in the study. Its value depends on or changes based on these factors.

Independent Category

: An independent category refers to a variable or factor that is not influenced by any other variables in the study. It stands alone and does not depend on any other factors.

Quantitative Variable

: A quantitative variable is a type of variable that represents numerical data and can be measured or counted. It provides information about quantities and amounts rather than qualities.

Two-Way Table

: A two-way table organizes categorical data for two variables and shows how they are related to each other.

2.3 Statistics for Two Categorical Variables

4 min readdecember 29, 2022

Athena_Codes

Athena_Codes

Athena_Codes

Athena_Codes

Attend a live cram event

Review all units live with expert teachers & students

Additional Relative Frequencies

Lets look back at the from Unit 2.2.

https://firebasestorage.googleapis.com/v0/b/fiveable-92889.appspot.com/o/images%2FScreen%20Shot%202020-04-24%20at%204.45-FOqnu1Kcf68e.png?alt=media&token=f3628028-5fa2-4796-bcb8-db51f591a524

Courtesy of Starnes, Daren S. and Tabor, Josh. The Practice of Statistics—For the AP Exam, 5th Edition. Cengage Publishing.

We can find more than just joint relative frequencies here as there’s also marginal relative frequencies and conditional relative frequencies. 😲

Marginal Relative Frequency

A marginal relative frequency is the relative frequency of all the people in a certain category. For example, the marginal relative frequency of a "50-50 chance” is 1416/4826 as from the right margin, we see that 1416 overall respondents gave that response. In other words, the marginal relative frequencies are the row and column totals in a divided by the total for the entire table. ➕

Conditional Relative Frequency

On the other hand, the conditional relative frequency is the frequency that we have of a particular category given the fact that we know a subject is in another category. The category that we know is called the given, or , while the other is called the , just like independent and dependent variables on graphs.

For example, the conditional frequency for “50-50 chance given male” is 720/2459 because out of the 2459 males who responded, 720 of them said “50-50 chance.” When calculating a conditional relative frequency, our denominator (or total) is usually considerably smaller than that of overall total. 🧱

Determining Associations from a Two-Way Table

From a , we can use marginal and conditional relative frequencies to consider if two categorical variables are associated or not. To do this, see if two corresponding conditional relative frequencies across different categories are not the same. This is also the same as seeing if the conditional relative frequency is not the same as the marginal relative frequency for the . This makes it so that certain values are more likely to yield a certain result than others. That is, we can predict behavior given the fact that we know that an individual falls under a certain category. 💍

Example

Using the above, we can determine that the variables "gender" and "opinion" are independent, or not associated, because the marginal relative frequency of being "50-50 chance" is roughly equal to the conditional relative frequency of being "50-50 chance given male".

https://firebasestorage.googleapis.com/v0/b/fiveable-92889.appspot.com/o/images%2FScreen%20Shot%202020-04-24%20at%204.57-uj3PWu8h12Zr.png?alt=media&token=7eef3de2-ec3f-4451-9260-88f4ff6cb242

🎥Watch: AP Stats - Probability: Two Way Tables, Independence, Tree Diagrams, etc

Vocabulary Practice from 2.1 to 2.3 Material

Match the number with the letter that corresponds to its description! 😁

1. Two-way tables

2, Side-by-side bar graphs

3. Mosaic plots

4. Segmented bar graphs

5.

6.

7.

8. Marginal relative frequency

9. Conditional relative frequency

A. A graphical display that shows the relationship between two categorical variables by dividing the area of a rectangle into tiles that represent the different categories of both variables.

B. A graphical display that shows the distribution of a by displaying the frequency or relative frequency of each category as a bar.

C. A graphical display that shows the relationship between two categorical variables by dividing the bars in a bar graph into segments that represent the different categories of one of the variables.

D. A statistical table that shows the frequencies or relative frequencies of two categorical variables in a cross-tabulated format, with one variable represented by rows and the other by columns.

E. A variable that can take on a limited number of categories or values, such as "male" or "female," but cannot be meaningfully ordered or measured on a continuous scale.

F. A variable that can be measured or ordered on a continuous scale, such as height or weight.

G. The relative frequency of a particular category of a within another category, calculated by dividing the frequency or relative frequency of the first category within the second category by the total frequency or relative frequency of the second category.

H. The frequency or relative frequency of a particular category of a , calculated by dividing the frequency or relative frequency of that category by the total frequency or relative frequency for the entire sample or population.

I. A statistical concept that refers to the relationship between two variables, often used to describe the association between two categorical variables.

Answers

1. D

2. B

3. A

4. C

5. E

6. F

7. I

8. H

9. G

Key Terms to Review (6)

Bivariate Variable

: A bivariate variable is a type of variable that involves two variables and examines their relationship with each other. It explores how changes in one variable affect the other.

Categorical Variable

: A categorical variable is one that represents characteristics or qualities rather than numerical values. It consists of categories or groups into which data can be classified.

Dependent Category

: A dependent category refers to a variable or factor that is influenced by other variables in the study. Its value depends on or changes based on these factors.

Independent Category

: An independent category refers to a variable or factor that is not influenced by any other variables in the study. It stands alone and does not depend on any other factors.

Quantitative Variable

: A quantitative variable is a type of variable that represents numerical data and can be measured or counted. It provides information about quantities and amounts rather than qualities.

Two-Way Table

: A two-way table organizes categorical data for two variables and shows how they are related to each other.


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© 2024 Fiveable Inc. All rights reserved.

AP® and SAT® are trademarks registered by the College Board, which is not affiliated with, and does not endorse this website.