CEVAP:

Goodness of fit tests are used to determine whether a data set comes from a particular distribution. Some null and alternative hypotheses examples about the population distributions are given below.

H0 : The population distribution is Normal Distribution

H1 : The population distribution is not Normal Distribution

H0 : The population distribution is Poisson Distribution

H1 : The population distribution is not Poisson Distribution

The most commonly used goodness of fit test is the chi-square goodness of fit test.

The chi-square goodness of fit test is based on a comparison of the observed frequencies with the expected frequencies. First of all, the data is classified into k classes. For the ith class, the observed frequency is denoted by Oi and the expected frequency is denoted by Ei. Sum of the observed and expected frequencies must be equal to the sample size n as shown in the following equations.