Goodness of Fit Test Explained
The question asks to identify the statistical test used to evaluate the 'goodness of fit' of a distribution. This means determining how well observed data matches an expected theoretical distribution.
Identifying the Correct Test
Among the given options, the Chi-square test is specifically designed for goodness-of-fit.
- Chi-square ($\chi^2$) Test: Compares observed frequencies in different categories to the frequencies that would be expected if a particular distribution model were true. It's used for categorical data and assessing distribution fit.
- F - test: Primarily used for comparing variances between two populations or in Analysis of Variance (ANOVA).
- Z - test and T - test: Typically used for comparing means between groups or testing hypotheses about population means when population standard deviation is known (Z-test) or unknown (T-test).
Therefore, the Chi-square test is the appropriate method for testing the 'goodness of fit' of a distribution.
Correct Answer: Chi-square testImportant Questions from Hypothesis testing
If α is the level of significance and if (1 − α) is increased, then the width of the confidence interval of mean:
The analysis of variance technique was introduced by:
The power of a test is:
The term ‘Analysis of variance’ was introduced by:
Which of the following can be applied as a goodness-of-fit test?
