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PSYCH 625 Learning Team Assignment Data

PSYCH 625 Week 1 Individual Assignment – Reliability and Validity Matrix

PSYCH 625 Week 1 Individual Assignment – Time to Practice (Parts A,B,C)

PSYCH 625 Week 1 Individual Assignment (histogram)

PSYCH 625 Week 2 Individual Assignment – Time to Practice (Parts A,B,C)

PSYCH 625 Week 2 Learning Team Assignment – Frequency Analysis

PSYCH 625 Week 3 Individual Assignment – Time to Practice (Parts A,B,C)

PSYCH 625 Week 3 Learning Team Assignment – Descriptive Analysis

PSYCH 625 Week 3 Learning Team Assignment – Hypothesis Testing Problem Worksheet

PSYCH 625 Week 4 Individual Assignment – Time to Practice (Parts A,B,C)

PSYCH 625 Week 4 Learning Team Assignment – One-way ANOVA

PSYCH 625 Week 5 Discussion Questions

PSYCH 625 Week 5 Individual Assignment – Time to Practice (Parts A,B,C)

PSYCH 625 Week 5 Learning Team Assignment – Linear regression

PSYCH 625 Week 6 Learning Team Assignment – Statistics project presentation (version 2)

PSYCH 625 Week 6 Learning Team Assignment – Statistics project presentation (version 2)

PSYCH 625 Week 6 Learning Team Assignment – Statistics project presentation

Raw score

*Z* score

68.0

?

?

–1.6

82.0

?

?

1.8

69.0

?

?

–0.5

85.0

?

?

1.7

72.0

?

3. Questions 3a through 3d are based on a distribution of scores with and the standard Draw a small picture to help you see what is required.

a. What is the probability of a score falling between a raw score of 70 and 80?

b. What is the probability of a score falling above a raw score of 80?

c. What is the probability of a score falling between a raw score of 81 and 83?

d. What is the probability of a score falling below a raw score of 63?

4. Jake needs to score in the top 10% in order to earn a physical fitness certificate. The class mean is 78 and the standard deviation is 5.5. What raw score does he need?

5. Who is the better student, relative to his or her classmates? Use the following table for information.

Math

Class mean

81

Class standard deviation

2

Reading

Class mean

87

Class standard deviation

10

Raw scores

Math score

Reading score

Average

Noah

85

88

86.5

Talya

87

81

84

*Z-*scores

* *

* *

Math score

Reading score

Average

Noah

Talya

From Salkind (2011). Copyright © 2012 SAGE. All Rights Reserved. Adapted with permission.

Part B

Some questions in Part B require that you access data from Using SPSS for Windows and Macintosh. This data is available on the student website under the Student Text Resources link.

The data for Exercises 6 and 7 are in the data file named Lesson 20 Exercise File 1. Answer Exercises 6 and 7 based on the following research problem:

Ann wants to describe the demographic characteristics of a sample of 25 individuals who completed a large-scale survey. She has demographic data on the participants’ gender (two categories), educational level (four categories), marital status (three categories), and community population size (eight categories).

6. Using IBM® SPSS® software, conduct a frequency analysis on the gender and marital status variables. From the output, identify the following:

a. Percent of men

b. Mode for marital status

c. Frequency of divorced people in the sample

7. Using IBM® SPSS® software, create a frequency table to summarize the data on the educational level variable.

The data for Exercise 8 is available in the data file named Lesson 21 Exercise File 1.

8. David collects anxiety scores from 15 college students who visit the university health center during finals week. Compute descriptive statistics on the anxiety scores. From the output, identify the following:

a. Skewness

b. Mean

c. Standard deviation

d. Kurtosis

From Green & Salkind (2011). Copyright © 2012 Pearson Education. All Rights Reserved. Adapted with permission.

Part C

**Complete** the questions below. Be specific and provide examples when relevant.

**Cite** any sources consistent with APA guidelines.

Question

Answer

What is the relationship between reliability and validity? How can a test be reliable but not valid? Can a test be valid but not reliable? Why or why not?

How does understanding probability help you understand statistics?

How could you use standard scores and the standard distribution to compare the reading scores of two students receiving special reading resource help and one student in a standard classroom who does not get special help?

In a standard normal distribution: What does a *z* score of 1 represent? What percent of cases fall between the mean and one standard deviation above the mean? What percent fall between the mean and –1 to +1 standard deviations from the mean? What percent of scores will fall between –3 and +3 standard deviations under the normal curve?

Time to Practice – Week Three

Complete both Part A and Part B below.

Some questions in Part A require that you access data from Statistics for People Who (Think They) Hate Statistics.This data is available on the student website under the Student Test Resources link.

1. For the following research questions, create one null hypothesis, one directional research hypothesis, and one nondirectional research hypothesis.

a. What are the effects of attention on out-of-seat classroom behavior?

b. What is the relationship between the quality of a marriage and the quality of the spouses’ relationships with their siblings?

c. What is the best way to treat an eating disorder?

2. Provide one research hypothesis and an equation for each of the following topics:

a. The amount of money spent on food among undergraduate students and undergraduate student-athletes

b. The average amount of time taken by white and brown rats to get out of a maze

c. The effects of Drug A and Drug B on a disease

d. The time to complete a task in Method 1 and Method 2

3. Why does the null hypothesis presume no relationship between variables?

4. Create a research hypothesis tested using a one-tailed test and a research hypothesis tested using a two-tailed test.

5. What does the critical value represent?

6. Given the following information, would your decision be to reject or fail to reject the null hypothesis? Setting the level of significance at .05 for decision making, provide an explanation for your conclusion.

a. The null hypothesis that there is no relationship between the type of music a person listens to and his crime rate (p < .05).

b. The null hypothesis that there is no relationship between the amount of coffee consumption and GPA (p = .62).

c. The null hypothesis that there is a negative relationship between the number of hours worked and level of job satisfaction (p = .51).

7. Why is it harder to find a significant outcome (all other things being equal) when the research hypothesis is being tested at the .01 rather than the .05 level of significance?

8. Why should we think in terms of “failing to reject” the null rather than just accepting it?

9. When is it appropriate to use the one-sample z test?

10. What similarity does a z test have to a simple z or standard score?

11. For the following situations, write out a research hypothesis:

a. Bob wants to know if the weight loss for his group on the chocolate-only diet is representative of weight loss in a large population of middle-aged men.

b. The health department is charged with finding out if the rate of flu per thousand citizens for this past flu season is comparable to the average rate of the past 50 seasons.

c. Blair is almost sure that his monthly costs for the past year are not representative of his average monthly costs over the past 20 years.

12. There were about 15 flu cases per week, this flu season, in the Oshkosh school system. The weekly average for the entire state is 16 and the standard deviation, is 2.35. Are the kids in Oshkosh as sick as the kids throughout the state?

From Salkind (2011). Copyright © 2012 SAGE. All Rights Reserved. Adapted with permission.

Part B

Complete the following questions. Be specific and provide examples when relevant.

Cite any sources consistent with APA guidelines.

Question

Answer

The average raw math achievement score for third graders at a Smith elementary school is 137; third graders statewide score an average of 124 with a standard deviation of 7. Are the Smith third graders better at math than third graders throughout the state? Perform the correct statistical test, applying the eight steps of the hypothesis testing process as demonstrated on pp. 185–187 of Statistics for People Who (Think they) Hate Statistics.

What is a research question that you would like to answer? Write the null and research hypotheses. Would you use a one- or two-tailed test? Why?

What do we mean when we say that a statistical result is significant? What is the difference between a statistically significant and a meaningful result? Why is statistical significance important?

Describe a Type I error for the previous study that compares third graders’ math achievement. Describe a Type II error for that study.

*Time to Practice – Week Four*

**Complete** Parts A, B, and C below.

Some questions in Part A require that you access data from *Statistics for People Who (Think **They) Hate Statistics**. *This data is available on the student website under the Student Text Resources link.

1. Using the data in the file named Ch. 11 Data Set 2, test the research hypothesis at the .05 level of significance that boys raise their hands in class more often than girls. Do this practice problem by hand using a calculator. What is your conclusion regarding the research hypothesis? Remember to first decide whether this is a one- or two-tailed test.

2. Using the same data set (Ch. 11 Data Set 2), test the research hypothesis at the .01 level of significance that there is a difference between boys and girls in the number of times they raise their hands in class. Do this practice problem by hand using a calculator. What is your conclusion regarding the research hypothesis? You used the same data for this problem as for Question 1, but you have a different hypothesis (one is directional and the other is nondirectional). How do the results differ and why?

3. Practice the following problems by hand just to see if you can get the numbers right. Using the following information, calculate the *t* test statistic.

a.

b.

c.

4. Using the results you got from Question 3 and a level of significance at .05, what are the two-tailed critical values associated with each? Would the null hypothesis be rejected?

5. Using the data in the file named Ch. 11 Data Set 3, test the null hypothesis that urban and rural residents both have the same attitude toward gun control. Use IBM® SPSS® software to complete the analysis for this problem.

6. A public health researcher tested the hypothesis that providing new car buyers with child safety seats will also act as an incentive for parents to take other measures to protect their children (such as driving more safely, child-proofing the home, and so on). Dr. L counted all the occurrences of safe behaviors in the cars and homes of the parents who accepted the seats versus those who did not. The findings: a significant difference at the .013 level. Another researcher did exactly the same study; everything was the same—same type of sample, same outcome measures, same car seats, and so on. Dr. R’s results were marginally significant (recall Ch. 9) at the .051 level. Which result do you trust more and why?

7. In the following examples, indicate whether you would perform a *t* test of independent means or dependent means.

a. Two groups were exposed to different treatment levels for ankle sprains. Which treatment was most effective?

b. A researcher in nursing wanted to know if the recovery of patients was quicker when some received additional in-home care whereas when others received the standard amount.

c. A group of adolescent boys was offered interpersonal skills counseling and then tested in September and May to see if there was any impact on family harmony.

d. One group of adult men was given instructions in reducing their high blood pressure whereas another was not given any instructions.

e. One group of men was provided access to an exercise program and tested two times over a 6-month period for heart health.

8. For Ch. 12 Data Set 3, compute the *t* value and write a conclusion on whether there is a difference in satisfaction level in a group of families’ use of service centers following a social service intervention on a scale from 1 to 15. Do this exercise using IBM® SPSS® software, and report the exact probability of the outcome.

9. Do this exercise by hand. A famous brand-name manufacturer wants to know whether people prefer Nibbles or Wribbles. They sample each type of cracker and indicate their like or dislike on a scale from 1 to 10. Which do they like the most?

Nibbles rating

Wribbles rating

9

4

3

7

1

6

6

8

5

7

7

7

8

8

3

6

10

7

3

8

5

9

2

8

9

7

6

3

2

6

5

7

8

6

1

5

6

5

3

6

10. Using the following table, provide three examples of a simple one-way ANOVA, two examples of a two-factor ANOVA, and one example of a three-factor ANOVA. Complete the table for the missing examples. Identify the grouping and the test variable.

Design

Grouping variable(s)

Test variable

Simple ANOVA

Four levels of hours of training—2, 4, 6, and 8 hours

Typing accuracy

*Enter Your Example Here*

*Enter Your Example Here*

*Enter Your Example Here*

*Enter Your Example Here*

*Enter Your Example Here*

*Enter Your Example Here*

Two-factor ANOVA

Two levels of training and gender (two-way design)

Typing accuracy

*Enter Your Example Here*

*Enter Your Example Here*

*Enter Your Example Here*

*Enter Your Example Here*

Three-factor ANOVA

Two levels of training, two of gender, and three of income

Voting attitudes

*Enter Your Example Here*

*Enter Your Example Here*

11. Using the data in Ch. 13 Data Set 2 and the IBM® SPSS® software, compute the *F* ratio for a comparison between the three levels representing the average amount of time that swimmers practice weekly (< 15, 15–25, and > 25 hours) with the outcome variable being their time for the 100-yard freestyle. Does practice time make a difference? Use the Options feature to obtain the means for the groups.

12. When would you use a factorial ANOVA rather than a simple ANOVA to test the significance of the difference between the averages of two or more groups?

13. Create a drawing or plan for a 2 × 3 experimental design that would lend itself to a factorial ANOVA. Identify the independent and dependent variables.

From Salkind (2011). Copyright © 2012 SAGE. All Rights Reserved. Adapted with permission.

Part B

Some questions in Part B require that you access data from Using SPSS for Windows and Macintosh. This data is available on the student website under the Student Text Resources link.

The data for Exercise 14 is in the data file named Lesson 22 Exercise File 1.

14. John is interested in determining if a new teaching method, the involvement technique, is effective in teaching algebra to first graders. John randomly samples six first graders from all first graders within the Lawrence City School System and individually teaches them algebra with the new method. Next, the pupils complete an eight-item algebra test. Each item describes a problem and presents four possible answers to the problem. The scores on each item are 1 or 0, where 1 indicates a correct response and 0 indicates a wrong response. The IBM® SPSS® data file contains six cases, each with eight item scores for the algebra test.

Conduct a one-sample *t* test on the total scores. On the output, identify the following:

a. Mean algebra score

b. *T* test value

c. *P* value

The data for Exercise 15 is in the data file named Lesson 25 Exercise File 1.

15. Marvin is interested in whether blonds, brunets, and redheads differ with respect to their extrovertedness. He randomly samples 18 men from his local college campus: six blonds, six brunets, and six redheads. He then administers a measure of social extroversion to each individual.

Conduct a one-way ANOVA to investigate the relationship between hair color and social extroversion. Conduct appropriate post hoc tests. On the output, identify the following:

a. *F* ratio for the group effect

b. Sums of squares for the hair color effect

c. Mean for redheads

d. *P* value for the hair color effect

From Green & Salkind (2011). Copyright © 2012 Pearson Education. All Rights Reserved. Adapted with permission.

**Complete** the questions below. Be specific and provide examples when relevant.

**Cite** any sources consistent with APA guidelines.

Question

Answer

What is meant by independent samples? Provide a research example of two independent samples.

When is it appropriate to use a *t* test for dependent samples? What is the key piece of information you must know in order to decide?

When is it appropriate to use an ANOVA? What is the key piece of information you must know in order to decide?

Why would you want to do an ANOVA when you have more than two groups, rather than just comparing each pair of means with a *t* test?

Time to Practice – Week Five

Complete Parts A, B, and C below.

Some questions in Part A require that you access data from Statistics for People Who (Think They) Hate Statistics. This data is available on the student website under the Student Text Resources link.

1. Use the following data to answer Questions 1a and 1b.

Total no. of problems correct (out of a possible 20)

Attitude toward test taking (out of a possible 100)

17

94

13

73

12

59

15

80

16

93

14

85

16

66

16

79

18

77

19

91

a. Compute the Pearson product-moment correlation coefficient by hand and show all your work.

b. Construct a scatterplot for these 10 values by hand. Based on the scatterplot, would you predict the correlation to be direct or indirect? Why?

2. Rank the following correlation coefficients on strength of their relationship (list the weakest first):

+.71

+.36

–.45

.47

–.62

3. Use IBM® SPSS® software to determine the correlation between hours of studying and grade point average for these honor students. Why is the correlation so low?

Hours of studying

GPA

23

3.95

12

3.90

15

4.00

14

3.76

16

3.97

21

3.89

14

3.66

11

3.91

18

3.80

9

3.89

4. Look at the following table. What type of correlation coefficient would you use to examine the relationship between ethnicity (defined as different categories) and political affiliation? How about club membership (yes or no) and high school GPA? Explain why you selected the answers you did.

Level of Measurement and Examples

Variable X

Variable Y

Type of correlation

Correlation being computed

Nominal (voting preference, such as Republican or Democrat)

Nominal (gender, such as male or female)

Phi coefficient

The correlation between voting preference and gender

Nominal (social class, such as high, medium, or low)

Ordinal (rank in high school graduating class)

Rank biserial coefficient

The correlation between social class and rank in high school

Nominal (family configuration, such as intact or single parent)

Interval (grade point average)

Point biserial

The correlation between family configuration and grade point average

Ordinal (height converted to rank)

Ordinal (weight converted to rank)

Spearman rank correlation coefficient

The correlation between height and weight

Interval (number of problems solved)

Interval (age in years)

Pearson product-moment correlation coefficient

The correlation between number of problems solved and the age in years

5. When two variables are correlated (such as strength and running speed), it also means that they are associated with one another. But if they are associated with one another, then why does one not cause the other?

6. Given the following information, use Table B.4 in Appendix B of Statistics for People Who (Think They) Hate Statistics to determine whether the correlations are significant and how you would interpret the results.

a. The correlation between speed and strength for 20 women is .567. Test these results at the .01 level using a one-tailed test.

b. The correlation between the number correct on a math test and the time it takes to complete the test is –.45. Test whether this correlation is significant for 80 children at the .05 level of significance. Choose either a one- or a two-tailed test and justify your choice.

c. The correlation between number of friends and grade point average (GPA) for 50 adolescents is .37. Is this significant at the .05 level for a two-tailed test?

7. Use the data in Ch. 15 Data Set 3 to answer the questions below. Do this one manually or use IBM®SPSS® software.

a. Compute the correlation between income and level of education.

b. Test for the significance of the correlation.

c. What argument can you make to support the conclusion that lower levels of education cause low income?

8. Use the following data set to answer the questions. Do this one manually.

a. Compute the correlation between age in months and number of words known.

b. Test for the significance of the correlation at the .05 level of significance.

c. Recall what you learned in Ch. 5 of Salkind (2011)about correlation coefficients and interpret this correlation.

Age in months

Number of words known

12

6

15

8

9

4

7

5

18

14

24

18

15

7

16

6

21

12

15

17

9. How does linear regression differ from analysis of variance?

10. Betsy is interested in predicting how many 75-year-olds will develop Alzheimer’s disease and is using level of education and general physical health graded on a scale from 1 to 10 as predictors. But she is interested in using other predictor variables as well. Answer the following questions.

a. What criteria should she use in the selection of other predictors? Why?

b. Name two other predictors that you think might be related to the development of Alzheimer’s disease.

c. With the four predictor variables (level of education, general physical health, and the two new ones that you name), draw out what the model of the regression equation would look like.

11. Joe Coach was curious to know if the average number of games won in a year predicts Super Bowl performance (win or lose). The x variable was the average number of games won during the past 10 seasons. The y variable was whether the team ever won the Super Bowl during the past 10 seasons. Refer to the following data set:

Team

Average no. of wins over 10 years

Bowl? ( and )

Savannah Sharks

12

1

Pittsburgh Pelicans

11

0

Williamstown Warriors

15

0

Bennington Bruisers

12

1

Atlanta Angels

13

1

Trenton Terrors

16

0

Virginia Vipers

15

1

Charleston Crooners

9

0

Harrisburg Heathens

8

0

Eaton Energizers

12

1

a. How would you assess the usefulness of the average number of wins as a predictor of whether a team ever won a Super Bowl?

b. What’s the advantage of being able to use a categorical variable (such as 1 or 0) as a dependent variable?

c. What other variables might you use to predict the dependent variable, and why would you choose them?

From Salkind (2011). Copyright © 2012 SAGE. All Rights Reserved. Adapted with permission.

Part B

Some questions in Part B require that you access data from Using SPSS for Windows and Macintosh. This data is available on the student website under the Student Text Resources link. The data for this exercise is in the data file named Lesson 33 Exercise File 1.

Peter was interested in determining if children who hit a bobo doll more frequently would display more or less aggressive behavior on the playground. He was given permission to observe 10 boys in a nursery school classroom. Each boy was encouraged to hit a bobo doll for 5 minutes. The number of times each boy struck the bobo doll was recorded (bobo). Next, Peter observed the boys on the playground for an hour and recorded the number of times each boy struck a classmate (peer).

1. Conduct a linear regression to predict the number of times a boy would strike a classmate from the number of times the boy hit a bobo doll. From the output, identify the following:

a. Slope associated with the predictor

b. Additive constant for the regression equation

c. Mean number of times they struck a classmate

d. Correlation between the number of times they hit the bobo doll and the number of times they struck a classmate

e. Standard error of estimate

From Green & Salkind (2011). Copyright © 2012 Pearson Education. All Rights Reserved. Adapted with permission.

Complete the questions below. Be specific and provide examples when relevant.

Cite any sources consistent with APA guidelines.

Question

Answer

Draw a scatterplot of each of the following:

· A strong positive correlation

· A strong negative correlation

· A weak positive correlation

· A weak negative correlation

Give a realistic example of each.

What is the coefficient of determination? What is the coefficient of alienation? Why is it important to know the amount of shared variance when interpreting both the significance and the meaningfulness of a correlation coefficient?

If a researcher wanted to predict how well a student might do in college, what variables do you think he or she might examine? What statistical procedure would he or she use?

What is the meaning of the p value of a correlation coefficient?