
Concept explainers
Most sports injuries are immediate and obvious, like a broken leg. However, some can be more subtle, like the neurological damage that may occur when soccer players repeatedly head a soccer ball. To examine effects of repeated heading. McAllister et al. (2013) examined a group of football and ice hockey players and a group of athletes in noncontact sports before and shortly after the season. The dependent variable was performance on a conceptual thinking task. Following are hypothetical data from an independent-measures study similar to the one by McAllister et al. The researchers measured conceptual thinking for contact and noncontact athletes at the beginning of their first season and for separate groups of athletes at the end of their second season.
- a. Use a two-factor ANOVA with α = .05 to evaluate the main effects and interactions.
- b. Calculate the effects size (η2) for the main effects and the interaction.
- c. Briefly describe the outcome of the study.
a.

Answer to Problem 23P
Both the main effects and interaction are significant.
Explanation of Solution
Given info:
Following data is given:
Factor B: Time | |||
Before the first season |
After the second season | ||
Factor A: Sport |
Contact sport |
|
|
Non contact support |
|
|
|
|
Calculation:
Let, k represent total numbers of treatment conditions.
Let N represent total numbers of observations. Then
Let G represent grand total. Then,
Evaluation of the main effect for factor A is:
The hypotheses are given below:
Null hypothesis: There is no difference between the two levels of factor A that is main effect for factor A is not significant.
Alternate hypothesis: There is significant difference between the two levels of factor A that is main effect for factor A is significant.
Degrees of freedom corresponding to
Degrees of freedom corresponding to:
Variability between treatments is given as:
Degrees of freedom corresponding to
F ratio is given as:
From the table in appendix B.4, the critical value corresponding to degrees of freedom
Since, F-ratio is greater than critical value, so reject the null hypothesis and conclude that there are significant differences between levels of factor A.
Evaluation of the main effect for factor B is:
The hypotheses are given below:
Null hypothesis: There is no difference between the two levels of factor B that is main effect for factor B is not significant.
Alternate hypothesis: There is significant difference between the two levels of factor B that is main effect for factor B is significant.
F ratio is given as:
From the table in appendix B.4, the critical value corresponding to degrees of freedom
Since, F-ratio is greater than critical value, so reject the null hypothesis and conclude that there are significant differences between levels of factor B that is main effect for factor B is significant.
Evaluation of the interaction is:
The hypotheses are given below:
Null hypothesis: There is no interaction between the two factors A and B.
Alternate hypothesis: There is no interaction between the two factors A and B.
F ratio is given as:
From the table in appendix B.4, the critical value corresponding to degrees of freedom
Since, F-ratio is greater than critical value, so reject the null hypothesis and conclude that there is significant interaction between factors A and B or interaction is significant.
Conclusion:
Both the main effects and interaction are significant.
b.

Answer to Problem 23P
The value of
The value of
The value of
Explanation of Solution
Calculation:
From part a.
The value of
The value of
The value of
Conclusion:
The value of
The value of
The value of
c.

Answer to Problem 23P
For contact sport athletes, there is a significant decrease in scores that is scores after the second season are less than the scores after the first session. For non-contact sport athletes, there is small decrease or no significant difference in scores after the second season.
Explanation of Solution
From the given info, for the contact support, mean scores before the first season and after the second season are 9 and 4 respectively. Therefore, there is a significant decrease in time after the second season corresponding to the contact sport.
From the given info, for the non-contact support, mean scores before the first season and after the second season are 9 and 8 respectively. Therefore, there is little bit decrease in time after the second season corresponding to the non-contact sport.
Conclusion:
For contact sport athletes, there is a significant decrease in scores corresponding to the factor time that is scores after the second season are less than the scores after the first session. For non-contact sport athletes, there is small decrease or no decrease in scores after the second season.
Want to see more full solutions like this?
Chapter 13 Solutions
Bundle: Essentials of Statistics for The Behavioral Sciences, Loose-Leaf Version, 9th + LMS Integrated Aplia, 1 term Printed Access Card
- Suppose we wish to test the hypothesis that women with a sister’s history of breast cancer are at higher risk of developing breast cancer themselves. Suppose we assume that the prevalence rate of breast cancer is 3% among 60- to 64-year-old U.S. women, whereas it is 5% among women with a sister history. We propose to interview 400 women 40 to 64 years of age with a sister history of the disease. What is the power of such a study assuming that the level of significance is 10%? I only need help writing the null and alternative hypotheses.arrow_forward4.96 The breaking strengths for 1-foot-square samples of a particular synthetic fabric are approximately normally distributed with a mean of 2,250 pounds per square inch (psi) and a standard deviation of 10.2 psi. Find the probability of selecting a 1-foot-square sample of material at random that on testing would have a breaking strength in excess of 2,265 psi.4.97 Refer to Exercise 4.96. Suppose that a new synthetic fabric has been developed that may have a different mean breaking strength. A random sample of 15 1-foot sections is obtained, and each section is tested for breaking strength. If we assume that the population standard deviation for the new fabric is identical to that for the old fabric, describe the sampling distribution forybased on random samples of 15 1-foot sections of new fabricarrow_forwardUne Entreprise œuvrant dans le domaine du multividéo donne l'opportunité à ses programmeurs-analystes d'évaluer la performance des cadres supérieurs. Voici les résultats obtenues (sur une échelle de 10 à 50) où 50 représentent une excellente performance. 10 programmeurs furent sélectionnés au hazard pour évaluer deux cadres. Un rapport Excel est également fourni. Programmeurs Cadre A Cadre B 1 34 36 2 32 34 3 18 19 33 38 19 21 21 23 7 35 34 8 20 20 9 34 34 10 36 34 Test d'égalité des espérances: observations pairéesarrow_forward
- A television news channel samples 25 gas stations from its local area and uses the results to estimate the average gas price for the state. What’s wrong with its margin of error?arrow_forwardYou’re fed up with keeping Fido locked inside, so you conduct a mail survey to find out people’s opinions on the new dog barking ordinance in a certain city. Of the 10,000 people who receive surveys, 1,000 respond, and only 80 are in favor of it. You calculate the margin of error to be 1.2 percent. Explain why this reported margin of error is misleading.arrow_forwardYou find out that the dietary scale you use each day is off by a factor of 2 ounces (over — at least that’s what you say!). The margin of error for your scale was plus or minus 0.5 ounces before you found this out. What’s the margin of error now?arrow_forward
- Suppose that Sue and Bill each make a confidence interval out of the same data set, but Sue wants a confidence level of 80 percent compared to Bill’s 90 percent. How do their margins of error compare?arrow_forwardSuppose that you conduct a study twice, and the second time you use four times as many people as you did the first time. How does the change affect your margin of error? (Assume the other components remain constant.)arrow_forwardOut of a sample of 200 babysitters, 70 percent are girls, and 30 percent are guys. What’s the margin of error for the percentage of female babysitters? Assume 95 percent confidence.What’s the margin of error for the percentage of male babysitters? Assume 95 percent confidence.arrow_forward
- You sample 100 fish in Pond A at the fish hatchery and find that they average 5.5 inches with a standard deviation of 1 inch. Your sample of 100 fish from Pond B has the same mean, but the standard deviation is 2 inches. How do the margins of error compare? (Assume the confidence levels are the same.)arrow_forwardA survey of 1,000 dental patients produces 450 people who floss their teeth adequately. What’s the margin of error for this result? Assume 90 percent confidence.arrow_forwardThe annual aggregate claim amount of an insurer follows a compound Poisson distribution with parameter 1,000. Individual claim amounts follow a Gamma distribution with shape parameter a = 750 and rate parameter λ = 0.25. 1. Generate 20,000 simulated aggregate claim values for the insurer, using a random number generator seed of 955.Display the first five simulated claim values in your answer script using the R function head(). 2. Plot the empirical density function of the simulated aggregate claim values from Question 1, setting the x-axis range from 2,600,000 to 3,300,000 and the y-axis range from 0 to 0.0000045. 3. Suggest a suitable distribution, including its parameters, that approximates the simulated aggregate claim values from Question 1. 4. Generate 20,000 values from your suggested distribution in Question 3 using a random number generator seed of 955. Use the R function head() to display the first five generated values in your answer script. 5. Plot the empirical density…arrow_forward
- Glencoe Algebra 1, Student Edition, 9780079039897...AlgebraISBN:9780079039897Author:CarterPublisher:McGraw HillBig Ideas Math A Bridge To Success Algebra 1: Stu...AlgebraISBN:9781680331141Author:HOUGHTON MIFFLIN HARCOURTPublisher:Houghton Mifflin HarcourtHolt Mcdougal Larson Pre-algebra: Student Edition...AlgebraISBN:9780547587776Author:HOLT MCDOUGALPublisher:HOLT MCDOUGAL


