1. CHI-SQUARE GOODNESS OF FIT TEST What Are Nonparametric Statistics? What is the Purpose of the Chi-Square GOF? What Are the Assumptions? How Does it Work?

2. What Are Nonparametric Statistics? Statistical tests such as the t-test and z-test are parametric because they test a hypothesis about a particular population value (parameter). Nonparametrics such as chi-square test a hypothesis, but not about one particular parameter.

3. What Are Nonparametric Statistics? Parametric statistics require assumptions that are often not satisfied (e.g., shape of the population distribution, interval/ratio data). Nonparametric statistics require assumptions, but they are easier to meet.

4. What is the Purpose of the Chi-Square Goodness of Fit? Test whether an observed frequency distribution differs from a Null Hypothesis frequency distribution. Use for a design in which individuals categorized into two or more groups.

5. What are the Assumptions? mutually exclusive groups expected frequencies at least 5 per cell

6. How Does it Work? Determine the frequencies you expect if the Ho is true. Compare the observed frequencies to the Ho expected frequencies. Large differences between observed and expected give a large value of chi-square, likely to be significant.