8.CHI SQUARE AND ANOVA(Meaning and explanation).pptx

Meaning and explanation

1. CHI SQUARE AND ANOVA Dr.S.Jayanthi Sobhana Asst.Professor , Department of commerce PA Sri Ramakrishna college of Arts & Science

2. Chi-Square Test: The Chi-Square test is a statistical test used to examine the association or independence between two categorical variables.  It compares the observed frequencies of each category with the expected frequencies under the assumption of independence. The test determines whether there is a significant relationship between the variables based on the discrepancies between observed and expected frequencies.

3. There are different variations of the Chi-Square test, such as the Chi-Square test for independence (to test if variables are independent) and the Chi-Square goodness-of-fit test (to test if observed frequencies fit an expected distribution).

4. ANOVA (Analysis of Variance): ANOVA is a statistical test used to determine if there are significant differences between the means of two or more groups.  It analyzes the variance within and between groups to assess whether the differences observed are due to random chance or actual group differences.

5. ANOVA is commonly used when you have a continuous dependent variable and one or more categorical independent variables with multiple levels.  The test compares the means across the groups and calculates an F-statistic and p-value to determine if the differences are statistically significant.

6. There are different types of ANOVA tests depending on the number of independent variables, such as one-way ANOVA, two-way ANOVA, and factorial ANOVA. Each test has its specific assumptions and requirements.