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Contingency Tables

by David Spade, PhD
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    About the Lecture

    The lecture Contingency Tables by David Spade, PhD is from the course Statistics Part 1. It contains the following chapters:

    • Contingency Tables
    • Marginal Distributions
    • Checking the Work
    • Conditional Distributions
    • Independence of Two Categorical Variables
    • Simpson's Paradox

    Included Quiz Questions

    1. A contingency table describes the distribution of two categorical variables at the same time.
    2. A contingency table describes the distribution of a categorical variable.
    3. A contingency table describes the distribution of two quantitative variables at the same time.
    4. None of the above is correct.
    1. The Marginal Distribution of the column variable can be obtained by looking at the column totals of the table.
    2. The Marginal Distribution of the row variable can be obtained by looking at the column totals of the table.
    3. The Marginal Distribution of the column variable can be obtained by looking at the row totals of the table.
    4. The table shows only what the distribution of one of the two variables looks like.
    1. We only talk about relative frequencies.
    2. We only talk about absolute frequencies.
    3. Here, we only pay attention to the observations that take the given value of the first variable.
    4. Here, we can not complete a check on our work by making sure that the percentages we came up with add up to 100%.
    1. Two categorial variables are independent if the conditional distribution of one variable is the same for all categories of the other.
    2. Two categorial variables are dependent if the conditional distribution of one variable is the same for all categories of the other.
    3. The easiest way to determine independence is to look at the conditional distribution of one variable for each category of the other.
    4. If two variables are not independent, we only need to show that two of the conditional distributions are different.
    1. Simpson’s Paradox occurs when looking at the data category-by-category in one of the variables paints a much different picture than looking at the data as a whole, such as relationships changing when we look at the data category-by-category in one variable.
    2. Simpson’s Paradox occurs when the data come out in a way that you do not expect.
    3. Simpson’s Paradox occurs when the marginal distributions of each of the two variables differ.
    4. Simpson’s Paradox occurs when the conditional distribution of one variable given one value of the other differs from the conditional variable of one variable given another value of the second variable.

    Author of lecture Contingency Tables

     David Spade, PhD

    David Spade, PhD


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