# For each of the following studies, say whether you would use a t-test for dependent means or a t test for independent means

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Homework 7
Chapter 10: 12, 14, 15
10.12 For each of the following studies, say whether you would use a t-test for dependent means or a t test for independent means.
a) A researcher measures the heights of 40 college students who are the first born in their families and compares the 15 who come from large families to the 25 who come from smaller families.

The two samples must be independent, so use a test of independent means.

b) A researcher tests performance on a math skills test of each of 250 individuals before and after they complete a one-day seminar on managing test anxiety.

Same people tested twice (“before and after”), so use a dependent samples test

c) A researcher compares the resting heart rate of 15 individuals who have been taking a particular drug to the resting heart rate of 48 other individuals who have not been taking this drug.

The two samples must be independent, so use a test of independent means.

10.14 For each of the following experiments, decide if the difference between conditions is statistically significant at the 0.05 level (two-tailed).

 a. 10 604 60 10 607 50 b. 40 604 60 40 607 50 c. 10 604 20 40 607 16

a)

-0.90 is not in the critical region (df= n1 + n2 – 2 = 18; tcrit = ±2.101), so we fail to reject the H0

b)

-1.81 is not in the critical region (df= n1 + n2 – 2 = 78; tcrit = ±2.0), so we fail to reject the H0

c)

-1.81 is not in the critical region (df= n1 + n2 – 2 = 18; tcrit = ±2.101), so we fail to reject the H0

1. A psychologist theorized that people can hear better when the have just eaten a large meal. Six individuals were randomly assigned to eat either a large meal or a small meal. After eating the meal, their hearing was tested. The hearing ability scores (high numbers indicate greater ability) are given below. Using the 0.05 level, do the results support the psychologist’s theory?

 Big Meal Group Small Meal Group Subject Hearing Subject Hearing A 22 D 19 B 25 E 23 C 25 F 21 mean 24 21 SS 6 8

1. Use the steps of hypothesis testing

H0: Hearing will be no different (or worse) for the group that ate a large meal ()

HA: Hearing will be better for the group that ate a large meal ()

-1.81 is not in the critical region (df= n1 + n2 – 2 = 4; tcrit = 2.132), so we fail to reject the H0

Conclude that the evidence does not support the claim that hearing is affected by meal size

1. Sketch the distributions involved

Answers will vary, should be something about how the observed difference between the groups is not above and beyond what you might expect based on random chance

1) Using SPSS, compute the correlation matrix which includes the following variables:

◦ average parents height

◦ income

◦ age

◦ weight

◦ height

Print out the correlation matrix and include it in your homework answers (or write it out).

Which of the correlations are statistically significant? Write out a description of each of these significant correlations.

Avg height of parents is significantly positively correlated with calcium intake (.52), weight (.66), and height (.80)

Household income is significantly positively correlated with age (.33)

Avg calcium intake is significantly positively correlated with height (.41)

Weight is significantly positively correlated with height (.79)

2) Compare a two regression models predicting height.

◦ Model 1: average parents height & calcium intake

◦ Model 2: average parents height, calcium intake, income, & weight

Describe each model (r-squared & whether the explanatory variables within each model are statistically significant). Also compute the change r-squared going from model 1 to model 2. Is this change statistically significant? What does this result suggest to you about selecting between model 1 and model 2?

 Model 1: average parents height & calcium intake r2 = 0.641 Variables Standardized betas t p avg parent height 0.81 6.98 <0.001 Avg calcium intake -0.01 0.07 0.941

These results suggest that Model 1 accounts for 64.1% of the variance in height, and that average parent height is the only variable that accounts for a significant amount of this variance (calcium intake doesn’t account for a significant amount of it)

 Model 2: average parents height, calcium intake, income, & weight r2 = 0.75 Variables Standardized betas t p avg parent height 0.456 3.77 <0.001 Avg calcium intake 0.028 0.30 0.765 Household income 0.087 1.07 0.294 Weight 0.475 4.44 <0.001

These results suggest that Model 2 accounts for 75% of the variance in height, and that average parent height and weigth are the only variables that account for a significant amount of this variance.

The change r2 statistic [F(2,35)=10.48, p < 0.001] suggests that the change in variance accounted for from Model 1 to Model 2 is statistically significant. So we may conclude that model 2 does a better job predicting height.

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