#1: Use the quantitative variable and just one of the categorical variables listed above. You choose which categorical variable from the list above you want to analyze.

#2: Use concepts to describe the distribution of the quantitative variable grouped by the categorical variable.

#3: Choose two or three groups of the categorical variable that are most interesting to compare.

Gender-Career IAT Variable Descriptions

Gender-Science IAT Variable Descriptions

Race IAT Variable Descriptions

Sexuality IAT Variable Descriptions

Weapons IAT Variable Descriptions

Weight IAT Variable Descriptions

#4: Then use percentages and descriptions of center and spread to make comparisons. What do the data suggest? For example, is a particular group from the categorical variable more likely to have a higher/lower IAT score?

Please answers the question from Question 1 TO Question 7. Thank you!!

Question 1: Stat-Crunch Stat-Crunch graphs and tables are correct and embedded with work.

Question 2: Graph The graph includes a meaningful title, variable descriptions, and a key for the numerical category labels below the graph.

Question 3: Summary Statistics Numerical categories were replaced with meaningful words in the table.

Question 4: Comparison Comparison correctly used percentages and descriptions of center and spread to make comparisons.

Question 5: Data Comparison correctly used the data to support answers to the questions "What do the data suggest?" and "Is a particular group from the categorical variable more likely to have a higher/lower IAT score?"

Question 6: Context The results were correctly interpreted in context.

Question 7:

The self-evaluation describes how we demonstrated attainment of the learning objectives in the "Progress Check" section the topic.

OR What we needed to correct in order to demonstrate achievement of the learning objectives.