Course Content

  • Z-Table, T-Table , Chi-Square Table

Course Content

FAQs

Goodness-of-fit tests assess how well sample data matches the population's expectations. An observed value is derived from the sample data and compared to the predicted expected value using a discrepancy measure.

Simply said, the greater the divergence between these numbers, the higher the chi square score, the more likely it is to be significant, and the more likely we will reject the null hypothesis and conclude the variables are related.

The chi-square test can be used for testing the strength of the association between two categorical variables (i.e., in terms of proportions) or two continuous variables (i.e., in terms of means and standard deviations).

A chi-square test is used to compare observed and expected frequencies for categorical variables. In this case, the categorical variable is whether or not a person has a given characteristic.

Chi-square is a statistical test that examines the differences between categorical variables from a random sample in order to determine if the expected and actual findings are well-fitting.

Recommended Courses

Share With Friend

Have a friend to whom you would want to share this course?

Download LearnVern App

App Preview Image
App QR Code Image
Code Scan or Download the app
Google Play Store
Apple App Store
598K+ Downloads
App Download Section Circle 1
4.57 Avg. Ratings
App Download Section Circle 2
15K+ Reviews
App Download Section Circle 3
  • Learn anywhere on the go
  • Get regular updates about your enrolled or new courses
  • Share content with your friends
  • Evaluate your progress through practice tests
  • No internet connection needed
  • Enroll for the webinar and join at the time of the webinar from anywhere