Question 1

1. Which IAT data set are you working with? Race IAT Variables
2. One sample T confidence interval:

: Mean of age

90% confidence interval results:

Variable	Sample Mean	Std. Err.	DF	L. Limit	U. Limit
Age	33.962867	0.55994083	699	33.040624	34.88511

1. Are conditions met to estimate the mean age for the population of IAT participants? (Be sure to support your answer as demonstrated throughout Unit 8.)
2. State the confidence interval, and then interpret the confidence interval in context.
3. What is the margin of error (MOE)?
4. Which would be more accurate, the 90% confidence interval you found or an 85% confidence interval? Briefly explain. Which would be more precise? Briefly explain.

Question 2

At the end of 2020, the mean age of the U.S. population was estimated to be 38.5 years old. You are tasked with determining whether the mean age of the population of IAT participants differs from the mean age of the U.S. population.

1. Let be the mean age of the population of Race IAT participants for your chosen IAT data set. State the hypotheses (symbolically and in words). Include a clear description of the populations and the variable.
2. Can we safely use the t-test with your IAT sample? Explain.
3. Perform the t-test using StatCrunch. Copy the information from the StatCrunch output window and paste it into your response.

One sample T hypothesis test:

: Mean of variable

H₀ : = 38.5

H_A : 38.5

Hypothesis test results:

Variable	Sample Mean	Std. Err.	DF	T-Stat	P-value
Sample(Age)	33.962867	0.55994083	699	-8.1028792	<0.0001

1. Based on the P-value, state your conclusions in context. Use a 5% level of significance. (NOTE: Since StatCrunch correctly calculates the P-value for either a one-tailed or a two-tailed test, you do not need to change the StatCrunch P-value.)
2. Using the context of this scenario, explain the meaning of each of the following items from the StatCrunch output for the hypothesis test. Std. Err (standard error) T-stat (T-score) P-value

Question 3

Quantitative Variable IAT-Race-Score: Score on the Race IAT

Categorical Variable Race: Subject's reported race: 5=Black or African American; 6=White (ignore all other races)

For all data sets, the categorical variable is the explanatory variable, and the quantitative variable is the response variable.

• Here is thequestion to be investigated for the two groups in your chosen categorical variable. Do the population of IAT participants in one group score higher on the IAT test than the population of IAT participants in the other group?

To answer the question we are investigating, respond to each of the following

1. Summary statistics for Sample(IAT-Race-Score):

Group by: Sample(Race)

Sample(Race)	n	Mean
5 = Black or African American	64	-0.17002983
6 = White	516	0.28339434

• Which of the two groups has the smallest sample mean? Which has the largest sample mean?
• Let 1 be the population mean for the group with the largest sample mean. Let 2 be the population mean for the group with the smallest sample mean. State the null and alternative hypotheses (symbolically and in words). Include a clear description of the populations and the variable.
• To test your hypotheses, is it appropriate to use the two-sample T-test? If so, explain why and provide any supporting evidence. If not, start over and choose the other categorical variable listed with your chosen IAT data set.
  • WARNING: If it is not appropriate to use the two-sample T-test for either of the categorical variables listed with your IAT data set, something may be wrong. Stop and contact me as soon as possible.
  • Proceed only if it is appropriate to use the two-sample T-test.
  • Two sample T hypothesis test:
• ₁ : Mean of Sample(IAT-Race-Score) where "Sample(Race)"=6
• ₂ : Mean of Sample(IAT-Race-Score) where "Sample(Race)"=5
• ₁ - ₂ : Difference between two means
• H₀ : ₁ - ₂ = 0
• H_A : ₁ - ₂ > 0
• (without pooled variances)
• Hypothesis test results:

Difference	Sample Diff.	Std. Err.	DF	T-Stat	P-value
1 - 2	0.45342417	0.056779128	81.522362	7.9857544	<0.0001

• Use a 5% significance level to state a conclusion. Be sure to state your conclusion in context and in terms of what a "more positive score" on the IAT means for your data set.