• Skip to secondary menu
  • Skip to main content
  • Skip to primary sidebar
  • My Store
  • Glossary
  • Home
  • About Me
  • Contact Me

Statistics By Jim

Making statistics intuitive

  • Graphs
  • Basics
  • Hypothesis Testing
  • Regression
  • ANOVA
  • Probability
  • Time Series
  • Fun

Conditional Distribution: Definition & Finding

By Jim Frost Leave a Comment

What is a Conditional Distribution?

A conditional distribution is a distribution of values for one variable that exists when you specify the values of other variables. This type of distribution allows you to assess the dispersal of your variable of interest under specific conditions, hence the name.

That might sound a bit complex, but the idea is straightforward.

Suppose you’re selling computers, and you record the type of computer and gender for each sale. Now imagine that you want to assess the dispersal of computer types for only female customers. That’s an example of a conditional distribution. We’re conditioning computer types on the gender variable value of female.

How to Find a Conditional Distribution

The process of conditioning one variable on the value of another variable might sound complicated. However, it’s simple to find a conditional distribution using a contingency table. Just look down a column or across a row.

The table below organizes our data for the computer type by gender study.

Contingency table that highlights the conditional distributions.

Related post: Contingency Tables: Definition, Examples & Interpreting

I highlight two examples in the table. Let’s stick with our original example of computer types for females. By looking at horizontal highlight in the table, we see that females have purchased the following:

  • PC: 30
  • Mac: 87

Statisticians say that you condition one variable on the value of another. In our example, we are conditioning computer type on the gender value of female. This process allows us to understand our data in a more specific context.

We could also assess a different conditional distribution to understand a different context, such as gender conditioned on Mac sales. That’s the vertical example I highlight in the contingency table above.

When you have conditional distributions, you can calculate conditional probabilities. For more information, read Using Contingency Tables to Calculate Probabilities.

A conditional distribution differs from a marginal distribution, which is the dispersal of one variable while disregarding all other variables.

Share this:

  • Tweet

Related

Filed Under: Basics Tagged With: conceptual, distributions

Reader Interactions

Comments and Questions Cancel reply

Primary Sidebar

Meet Jim

I’ll help you intuitively understand statistics by focusing on concepts and using plain English so you can concentrate on understanding your results.

Read More...

Buy My Introduction to Statistics Book!

Cover of my Introduction to Statistics: An Intuitive Guide ebook.

Buy My Hypothesis Testing Book!

Cover image of my Hypothesis Testing: An Intuitive Guide ebook.

Buy My Regression Book!

Cover for my ebook, Regression Analysis: An Intuitive Guide for Using and Interpreting Linear Models.

Subscribe by Email

Enter your email address to receive notifications of new posts by email.

    I won't send you spam. Unsubscribe at any time.

    Follow Me

    • FacebookFacebook
    • RSS FeedRSS Feed
    • TwitterTwitter

    Top Posts

    • How to Interpret P-values and Coefficients in Regression Analysis
    • How To Interpret R-squared in Regression Analysis
    • Multicollinearity in Regression Analysis: Problems, Detection, and Solutions
    • How to do t-Tests in Excel
    • How to Interpret the F-test of Overall Significance in Regression Analysis
    • Z-table
    • How to Find the P value: Process and Calculations
    • Mean, Median, and Mode: Measures of Central Tendency
    • Understanding Interaction Effects in Statistics
    • F-table

    Recent Posts

    • Sampling Frame: Definition & Examples
    • Probability Mass Function: Definition, Uses & Example
    • Using Scientific Notation
    • Selection Bias: Definition & Examples
    • ANCOVA: Uses, Assumptions & Example
    • Fibonacci Sequence: Formula & Uses

    Recent Comments

    • Morris on Validity in Research and Psychology: Types & Examples
    • Jim Frost on What are Robust Statistics?
    • Allan Fraser on What are Robust Statistics?
    • Steve on Survivorship Bias: Definition, Examples & Avoiding
    • Jim Frost on Using Post Hoc Tests with ANOVA

    Copyright © 2023 · Jim Frost · Privacy Policy