BTM8107-8 Week 6 Apply Repeated-Measures Correct Answers
Explores repeated-measures analysis techniques with verified solutions.
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BTM8107-8 Week 6 Apply Repeated-Measures Correct Answers
Activity #6 consists of two parts. In the first part, you will utilize an existing dataset to analyze the
dataset from repeated-measures experimental design. All SPSS output should be pasted into your Word
document. In the second part, you will be asked to create a dataset for a hypothetical repeated-
measures experimental design. Finally, you will answer questions about your hypothetical dataset.
Part A. SPSS Activity
The “Activity 6.sav” file contains a dataset of a high school teacher interested in determining whether his
students’ test scores increase over the course of a 12 week period. In the dataset, you will find the
following variables:
Participant: unique identifier
Gender: Male (M) or Female (F)
Score_0 – score on the initial course pre-test (first day of class)
Score_2 – score at the end of week 2
Score_4 – score at the end of week 4
Score_6 – score at the end of week 6
Score_8 – score at the end of week 8
Score_10 – score at the end of week 10
Score_12 – score at the end of the course (week 12)
To complete this Activity
1. Exploratory Data Analysis.
a. Perform exploratory data analysis on the relevant variables in the dataset. When possible, include
appropriate graphs to help illustrate the dataset.
b. Compose a one to two paragraph write up of the data.
c. Create an APA style table that presents descriptive statistics for the sample.
2. Repeated-Measures ANOVA. Perform a repeated-measures ANOVA using the “Activity 6.sav” data set.
You will use Score_0 through
Score_12 as your repeated measure (7 levels), and gender as a fixed factor.
a. Is the assumption of sphericity violated? How can you tell? What does this mean in the context of
interpreting the results?
b. Is there a main effect of gender? If so, explain the effect. Use post hoc tests when necessary or
explain why they are not required in this specific case.
c. Is there a main effect time (i.e., an increase in scores from Week 0 to Week 12)? If so, explain the
effect. Use post hoc tests when necessary or explain why they are not required in this specific case.
Examine the output carefully and give as much detail as possible in your findings.
d. Write up the results in APA style and interpret them. Be sure that you discuss both main effects and
the presence/absence of an interaction between the two.
Part B. Applying Analytical Strategies to an Area of Research Interest
3. Briefly restate your research area of interest.
a. Identify at least 2 variables for which you would utilize a repeated-measures ANOVA in your analysis.
Describe the variables and their scale of measurement. Identify whether each factor is fixed or repeating.
Where on the SPSS output would you look to find out if you violated the assumption of sphericity? If the
data did violate this assumption, what would the impact be on your analysis?
Activity #6 consists of two parts. In the first part, you will utilize an existing dataset to analyze the
dataset from repeated-measures experimental design. All SPSS output should be pasted into your Word
document. In the second part, you will be asked to create a dataset for a hypothetical repeated-
measures experimental design. Finally, you will answer questions about your hypothetical dataset.
Part A. SPSS Activity
The “Activity 6.sav” file contains a dataset of a high school teacher interested in determining whether his
students’ test scores increase over the course of a 12 week period. In the dataset, you will find the
following variables:
Participant: unique identifier
Gender: Male (M) or Female (F)
Score_0 – score on the initial course pre-test (first day of class)
Score_2 – score at the end of week 2
Score_4 – score at the end of week 4
Score_6 – score at the end of week 6
Score_8 – score at the end of week 8
Score_10 – score at the end of week 10
Score_12 – score at the end of the course (week 12)
To complete this Activity
1. Exploratory Data Analysis.
a. Perform exploratory data analysis on the relevant variables in the dataset. When possible, include
appropriate graphs to help illustrate the dataset.
b. Compose a one to two paragraph write up of the data.
c. Create an APA style table that presents descriptive statistics for the sample.
2. Repeated-Measures ANOVA. Perform a repeated-measures ANOVA using the “Activity 6.sav” data set.
You will use Score_0 through
Score_12 as your repeated measure (7 levels), and gender as a fixed factor.
a. Is the assumption of sphericity violated? How can you tell? What does this mean in the context of
interpreting the results?
b. Is there a main effect of gender? If so, explain the effect. Use post hoc tests when necessary or
explain why they are not required in this specific case.
c. Is there a main effect time (i.e., an increase in scores from Week 0 to Week 12)? If so, explain the
effect. Use post hoc tests when necessary or explain why they are not required in this specific case.
Examine the output carefully and give as much detail as possible in your findings.
d. Write up the results in APA style and interpret them. Be sure that you discuss both main effects and
the presence/absence of an interaction between the two.
Part B. Applying Analytical Strategies to an Area of Research Interest
3. Briefly restate your research area of interest.
a. Identify at least 2 variables for which you would utilize a repeated-measures ANOVA in your analysis.
Describe the variables and their scale of measurement. Identify whether each factor is fixed or repeating.
Where on the SPSS output would you look to find out if you violated the assumption of sphericity? If the
data did violate this assumption, what would the impact be on your analysis?
Your submittal should demonstrate thoughtful consideration of the ideas and concepts that are presented
in the course and provide new thoughts and insights relating directly to this topic. Where applicable your
submittal should reflect scholarly writing and current APA standards.
Review APA Form and Style.
Be sure to adhere to Northcentral University's Academic Integrity Policy. View the Northcentral Academic
Integrity Tutorial to refresh your knowledge of how to achieve academic integrity.
Upload your assignment using the Upload Assignment button below.
Learning Outcomes
2.0 Develop appropriate null and alternative hypotheses given a research question.
3.0 Calculate and interpret descriptive statistical analysis.
4.0 Create and interpret visual displays of data.
5.0 Apply appropriate statistical tests based on level of measurement.
6.0 Determine the appropriate use of inferential statistical analysis.
9.0 Compare and contrast parametric and non-parametric data analysis in order to apply the correct
statistical procedure.
10.0 Demonstrate proficiency in the use of SPSS.
11.0 Demonstrate proficiency in reporting statistical output in APA format.
in the course and provide new thoughts and insights relating directly to this topic. Where applicable your
submittal should reflect scholarly writing and current APA standards.
Review APA Form and Style.
Be sure to adhere to Northcentral University's Academic Integrity Policy. View the Northcentral Academic
Integrity Tutorial to refresh your knowledge of how to achieve academic integrity.
Upload your assignment using the Upload Assignment button below.
Learning Outcomes
2.0 Develop appropriate null and alternative hypotheses given a research question.
3.0 Calculate and interpret descriptive statistical analysis.
4.0 Create and interpret visual displays of data.
5.0 Apply appropriate statistical tests based on level of measurement.
6.0 Determine the appropriate use of inferential statistical analysis.
9.0 Compare and contrast parametric and non-parametric data analysis in order to apply the correct
statistical procedure.
10.0 Demonstrate proficiency in the use of SPSS.
11.0 Demonstrate proficiency in reporting statistical output in APA format.
BTM8107-8 week 6 Apply Repeated-Measures correct answers
Activity #6 consists of two parts. In the first part, you will utilize an existing dataset to analyze the
dataset from repeated-measures experimental design. All SPSS output should be pasted into your Word
document. In the second part, you will be asked to create a dataset for a hypothetical repeated-
measures experimental design. Finally, you will answer questions about your hypothetical dataset.
Part A. SPSS Activity
The “Activity 6.sav” file contains a dataset of a high school teacher interested in determining whether his
students’ test scores increase over the course of a 12 week period. In the dataset, you will find the
following variables:
Participant: unique identifier
Gender: Male (M) or Female (F)
Score_0 – score on the initial course pre-test (first day of class)
Score_2 – score at the end of week 2
Score_4 – score at the end of week 4
Score_6 – score at the end of week 6
Score_8 – score at the end of week 8
Score_10 – score at the end of week 10
Score_12 – score at the end of the course (week 12)
Activity #6 1. Exploratory Data Analysis. a. Perform exploratory data analysis on the relevant variables in
the dataset. When possible, include appropriate graphs to help illustrate the dataset.
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
Pre-test score 12 16 59 29.58 12.221
Week 2 score 12 22 60 33.08 10.113
Week 4 score 12 27 63 35.42 9.885
Week 6 score 12 20 60 35.67 10.671
Week 8 score 12 28 65 39.92 9.718
Week 10 score 12 33 67 45.67 8.690
Week 12 score 12 34 73 50.00 10.189
Valid N (listwise) 12
Activity #6 consists of two parts. In the first part, you will utilize an existing dataset to analyze the
dataset from repeated-measures experimental design. All SPSS output should be pasted into your Word
document. In the second part, you will be asked to create a dataset for a hypothetical repeated-
measures experimental design. Finally, you will answer questions about your hypothetical dataset.
Part A. SPSS Activity
The “Activity 6.sav” file contains a dataset of a high school teacher interested in determining whether his
students’ test scores increase over the course of a 12 week period. In the dataset, you will find the
following variables:
Participant: unique identifier
Gender: Male (M) or Female (F)
Score_0 – score on the initial course pre-test (first day of class)
Score_2 – score at the end of week 2
Score_4 – score at the end of week 4
Score_6 – score at the end of week 6
Score_8 – score at the end of week 8
Score_10 – score at the end of week 10
Score_12 – score at the end of the course (week 12)
Activity #6 1. Exploratory Data Analysis. a. Perform exploratory data analysis on the relevant variables in
the dataset. When possible, include appropriate graphs to help illustrate the dataset.
Descriptive Statistics
N Minimum Maximum Mean Std. Deviation
Pre-test score 12 16 59 29.58 12.221
Week 2 score 12 22 60 33.08 10.113
Week 4 score 12 27 63 35.42 9.885
Week 6 score 12 20 60 35.67 10.671
Week 8 score 12 28 65 39.92 9.718
Week 10 score 12 33 67 45.67 8.690
Week 12 score 12 34 73 50.00 10.189
Valid N (listwise) 12
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Document Details
University
Northcentral University
Subject
Statistics