Students Should Recognize the Three Different Data Structures and Be

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The Answer is The first category corresponds to descriptive research, for which the purpose is usually to describe a group of participants or the larger population that they represent. For numerical scores, this typically involves computing the mean and standard deviation. For scores from other measurement scales, the description usually consists of the proportion or percentage of individuals in each category on the scale of measurement.
The second category corresponds to correlational research, for which the goal is usually to describe and evaluate the relationship between variables, specifically to describe the relationship between pairs of variables. For numerical scores, this usually involves computing the Pearson correlation and then evaluating the significance of the correlation. For non-numerical scores, alternative correlations (Spearman, point-biserial, or phi coefficient) can be used to describe the relationship and a chi-square test for independence is often used to evaluate the significance of the relationship.
The third category corresponds to experimental and non-experimental research, for which the goal is usually to describe and evaluate the differences between groups. For numerical scores, this typically involves computing means and standard deviations to describe each group of scores and then using a t test or analysis of variance to evaluate the significance of the mean differences. For non-numerical scores, the differences are often described by comparing the proportions or the ranks from one group to another and the significance of the differences is established with a chi-square test for independence.
If the scores are ranks (or can be ranked), then there are special tests presented in Appendix E that can be used to evaluate the significance of the differences between groups.

Students Should Recognize the Three Different Data Structures and Be

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