Related Experiment Video

Updated: Aug 5, 2026

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies
10:50

Using the FishSim Animation Toolchain to Investigate Fish Behavior: A Case Study on Mate-Choice Copying In Sailfin Mollies

Published on: November 8, 2018

Testing marginal homogeneity in square tables; with emphasis on matched data

M A Moussa

    Computer Programs in Biomedicine
    |January 1, 1985
    PubMed

    More Related Videos

    Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design07:40

    Validation of a Psychosocial Intervention on Body Image in Older People: An Experimental Design

    Published on: May 31, 2021

    The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups14:14

    The Innovation Arena: A Method for Comparing Innovative Problem-Solving Across Groups

    Published on: May 13, 2022

    Related Concept Videos

    Test for Homogeneity01:23

    Test for Homogeneity

    The goodness–of–fit test can be used to decide whether a population fits a given distribution, but it will not suffice to decide whether two populations follow the same unknown distribution. A different test, called the test for homogeneity, can be used to conclude whether two populations have the same distribution. To calculate the test statistic for a test for homogeneity, follow the same procedure as with the test of independence. The hypotheses for the test for homogeneity can be stated as...
    One-Way ANOVA: Equal Sample Sizes01:15

    One-Way ANOVA: Equal Sample Sizes

    One-Way ANOVA can be performed on three or more samples with equal or unequal sample sizes. When one-way ANOVA is performed on two datasets with samples of equal sizes, it can be easily observed that the computed F statistic is highly sensitive to the sample mean.
    Different sample means can result in different values for the variance estimate: variance between samples. This is because the variance between samples is calculated as the product of the sample size and the variance between the...
    Sign Test for Matched Pairs01:17

    Sign Test for Matched Pairs

    The sign test for matched pairs offers a robust method for comparing two paired samples, often for the effects of an intervention in one of them. This method is very useful in situations where the underlying distribution of the data is unknown. The test compares two related samples—often pre- and post-treatment measurements on the same subjects—to determine if there are significant differences in their median values.
    To conduct the sign test, we first calculate the differences in value between...
    Wilcoxon Signed-Ranks Test for Matched Pairs01:09

    Wilcoxon Signed-Ranks Test for Matched Pairs

    The Wilcoxon signed-rank test for matched pairs evaluates the null hypothesis by combining the ranks of differences with their signs. It essentially tests whether the median of the differences in a population of matched pairs is zero. Since the test incorporates more information than the sign test, it generally yields more trustable conclusions. This test also does not require the data to follow a normal distribution, but two conditions must be met for it to be applicable: (1) the data must...
    Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test01:09

    Statistical Methods to Analyze Parametric Data: Student t-Test and Goodness-of-Fit Test

    In parametric statistics, two fundamental tests stand out for their utility and wide application: the Student's t-test and goodness-of-fit tests. These tests provide researchers with a robust method for drawing insights from data, testing hypotheses, and making informed decisions based on their findings.
    The Student's t-test is a statistical test that examines if there is a statistically significant difference between the means of two groups. This test is instrumental when dealing with data...
    McNemar's Test01:23

    McNemar's Test

    McNemar's Test is a nonparametric statistical test used to determine if there is a significant difference in proportions between two related groups when the outcome is binary (e.g., yes/no, success/failure). It is beneficial when we have paired data, such as pre-test/post-test designs, where the same subjects are measured under two different conditions. The test is named after the statistician Quinn McNemar, who introduced it in 1947. It is commonly used in situations where subjects are...