Chi-square Test | Explanation & Problems Solution | Two Columns | Statistics | Research Methodology

Chi-square Test - Explanation & Problems Solution - Two Columns - Statistics - Research Methodology

In this video you will be able to learn about the concept of chi-square test and how to solve problems of chi-square test in testing hypotheses. Step by step you will come to know the proper calculation of chi-square test. Besides how to make comment or make decision after calculation it will be also cleared to you after watching this video. It will also help you to understand how to use chi-square distribution table as well.

A chi-squared test (also chi-square or χ2 test) is a statistical hypothesis test that is valid to perform when the test statistic is chi-squared distributed under the null hypothesis, specifically Pearson's chi-squared test and variants thereof. Pearson's chi-squared test is used to determine whether there is a statistically significant difference between the expected frequencies and the observed frequencies in one or more categories of a contingency table. In the standard applications of this test, the observations are classified into mutually exclusive classes. If the null hypothesis that there are no differences between the classes in the population is true, the test statistic computed from the observations follows a χ2 frequency distribution. The purpose of the test is to evaluate how likely the observed frequencies would be assuming the null hypothesis is true.

#chi_square #chi_square_test #chi_square_problems_solution
#statistics #research_methodology

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