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Related Concept Videos

Life Tables01:22

Life Tables

A life table is a statistical tool that summarizes the mortality and survival patterns of a population, providing detailed insights into the likelihood of survival or death across different age intervals within a cohort. By organizing data on survival probabilities and mortality rates, life tables offer a clear snapshot of population dynamics over time. They are extensively used in demography, public health, actuarial science, and ecology to analyze life expectancy, design health interventions,...
Odds Ratio01:09

Odds Ratio

The odds ratio (OR) is a statistical measure used extensively in epidemiology and research to quantify the strength of association between exposure and outcome across different groups. Unlike relative risk, which compares the probabilities of an event occurring, the odds ratio compares the odds of an event occurring in the exposed group to the odds of it occurring in the unexposed group. The odds, in this context, are calculated as the probability of the event happening divided by the...
Applications of Life Tables01:22

Applications of Life Tables

Life tables are versatile across various fields, providing a quantitative basis for analyzing mortality and survival rates. Whether used by demographers, actuaries, epidemiologists, or sociologists, life tables offer valuable insights into the dynamics of life and death, facilitating informed decisions in public health, insurance, conservation, and beyond. Their broad applicability highlights the interconnectedness of demographic data with practical outcomes in everyday life and strategic...
Introduction to Test of Independence01:21

Introduction to Test of Independence

In statistics, the term independence means that one can directly obtain the probability of any event involving both variables by multiplying their individual probabilities. Tests of independence are chi-square tests involving the use of a contingency table of observed (data) values.
The test statistic for a test of independence is similar to that of a goodness-of-fit test:
Contingency Table01:29

Contingency Table

A contingency table provides a way of portraying data that can facilitate calculating probabilities. It is a method of displaying a frequency distribution as a table with rows and columns to show how two variables may be dependent (contingent) upon each other; The table helps determine conditional probabilities quite quickly and can help systematically organize, analyze and quantify data. The table displays sample values concerning two variables that may be dependent or contingent on one...
Hypothesis Test for Test of Independence01:16

Hypothesis Test for Test of Independence

The test of independence is a chi-square-based test used to determine whether two variables or factors are independent or dependent. This hypothesis test is used to examine the independence of the variables. One can construct two qualitative survey questions or experiments based on the variables in a contingency table. The goal is to see if the two variables are unrelated (independent) or related (dependent). The null and alternative hypotheses for this test are:
H0: The two variables (factors)...

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Related Experiment Video

Updated: May 27, 2026

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
06:49

Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

Published on: December 11, 2015

Mobility ratios and association in mobility tables.

A Tyree

    Population Studies
    |November 19, 2011
    PubMed
    Summary

    Sociologists struggled to compare occupational mobility data due to differing category sizes and dissimilar generational occupational distributions. They needed a method to make historical occupational structures comparable.

    Area of Science:

    • Sociology
    • Social Stratification
    • Demography

    Background:

    • Researchers in the late 1940s encountered challenges analyzing intergenerational occupational mobility data.
    • Key figures like Natalie Rogoff, David Glass, and Gosta Carlsson faced similar issues across different countries.

    Purpose of the Study:

    • To address the problem of comparing occupational mobility data when occupational categories vary significantly in size.
    • To develop a technique for making occupational structures from different time periods (generations) comparable.

    Main Methods:

    • Converting frequency matrices of father's occupation by respondent's occupation into inflow and outflow percentages.
    • Identifying the methodological challenge of comparing these percentages across dissimilar occupational categories.

    Related Experiment Videos

    Last Updated: May 27, 2026

    Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment
    06:49

    Evaluation of a Smartphone-based Human Activity Recognition System in a Daily Living Environment

    Published on: December 11, 2015

    Main Results:

    • The core problem stemmed from the unequal sizes of occupational categories, hindering direct comparison of mobility patterns.
    • Dissimilar marginal distributions between father and respondent generations, due to factors like differential fertility and occupational shifts, complicated analysis.

    Conclusions:

    • A standardized method was needed to adjust for differing occupational category sizes and generational occupational structure disparities.
    • The goal was to enable meaningful comparisons of social mobility across different populations and time periods.