Chi-square tests are nonparametric tests that examine nominal categories as

Chi-square tests are nonparametric tests that examine nominal categories as opposed to numerical values. Consider a situation in which you may want to transform numerical scores into categories. Provide a specific example of a situation in which categories are more informative than the actual values.

Suppose we had conducted an ANOVA, with individuals grouped by political affiliation (Republican, Democrat, and Other), and we were interested in how satisfied they were with the current administration.  Satisfaction was measured on a scale of 1-10, so it was measured on a continuous scale.  Explain what changes would be required so that you could analyze the hypothesis using a chi-square test. For instance, rather than looking at test scores as a range from 0 to 100, you could change the variable to low, medium, or high. What advantages and disadvantages do you see in using this approach? Which is the better option for this hypothesis, the parametric approach or nonparametric approach? Why?”

Justify your answers with appropriate reasoning and research from your textbook and course readings. Start reviewing and responding to at least two of your classmates as early in the week as possible. You can ask technical questions or respond generally to the overall experience. Be honest, clear, and concise. Always use constructive language, even in criticism, to work toward the goal of positive progress. Using questions and seeking clarifications are good ways to make your reviews substantive!

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