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## Statistics and probability

### Course: Statistics and probability>Unit 1

Lesson 3: Distributions in two-way tables

# Marginal and conditional distributions

Marginal distributions are totals for each row or column in a two-way table (or joint distribution table), showing the distribution of one variable. Conditional distributions show the distribution of one variable given a condition on the other. They're usually in percentages.

## Want to join the conversation?

• i dont understand this at all. i need serious help
• From what I've understood, marginal distribution is the percentage of a certain margin/bucket over the total. Conditional distribution is observing the data following the given condition.
• I thought that I understood, but once I got to the exercise, i got none of them correct.
• That's actually such a classic
• Why do we need to find Marginal and Conditional Distribution?
• They are both different types of relative frequency and they both have two different functions.
• Is marginal distribution just the percentage of a certain margin or bucket out of the total? For reference, Sal starts talking about marginal distributions at
• Well, basically yes. A marginal distribution is the percentages out of totals, and conditional distribution is the percentages out of some column.

UPD: Marginal distribution is the probability distribution of the sums of rows or columns expressed as percentages out of grand total. Conditional distribution, on the other hand, is the probability distribution of certain values in the table expressed as percentages out of sums (or local totals) of certain rows or columns. So you're basically going one level down here. These row and column totals is what's given in the conditional distribution. Intuitively, when you here the word given, think of it as your new total, out of which you'll calculate the percentage or the probability.

Hope this clears things out!
• So the name "marginal" here, is from being the edge of the table ?
• Yes that would be correct.
• I kind of think of it like, marginal distribution is the distribution of one factor and conditional is two or more factors or circumstances in the data collected in the table.
• at , why do we need to know about the other types of distributions?
• Well, from what I see, you need to know about different types of distributions, to gain more knowledge, so you can build off of that knowledge...