References:

#1: Analyze the relationship between two categorical variables using a two-way table.

#2: Analyze and compare risks using conditional probabilities.

#3: Nterpret probability distributions for a categorical variable.

#4: Distinguish between discrete quantitative variables and continuous quantitative variables.

The row and column labels in the contingency table are numbers.

Name row variable: Birth-Gender 1- Female

2- Male

Name column variable: Impressions.

Colum

1. Birth Gender

2. born female

3. moderately agree female

4. born male

5. moderately agree male

6. neither agree nor dislike

7. (total row)

Contingency table results:

Rows: Birth-Gender

Columns: Impression

	1	2	3	4	5	6	7	Total
1	239	65	13	16	22	6	4	365
2	562	168	40	46	51	10	7	884
Total	801	233	53	62	73	16	11	1249

For each of the following percentage questions. Then find the indicated percentage. Write each percent as a ratio (e.g. 25 out of 40) and as a percentage (e.g. 25/40 = 62.5%). Then interpret the percentage in a sentence.

Question 1 Find the percentage of Race IAT participants who were born female.

Question 2 Find the percentage of Race IAT participants who indicated that they moderately or strongly agree that it makes sense to use your knowledge of a person's racial group to form an impression of them.

Question 3 Find the percentage of Race IAT participants who were born male who moderately or strongly agree that it makes sense to use your knowledge of a person's racial group to form an impression of them.

Question 4 Find the percentage of Race IAT participants who neither agree nor disagree that it makes sense to use your knowledge of a person's racial group to form an impression of them were born female.

Question 5 Race IAT: Are born-female participants more likely to indicate that they strongly disagree that it makes sense to use your knowledge of a person's racial group to form an impression of them ( know about them is their race)?

Question 6 Use the Race IAT variable descriptions link to peruse the variables in your IAT data set. Unique data set contain any continuous random variables? If so, give an example and explain why the variable is a continuous random variable. If not, explain why not?

Question 7 Use the Race IAT variable descriptions Unique data set contain any discrete random variables? If so, give an example and explain why the variable is a discrete random variable. If not, explain why not?