1.Include an APA title block with your name, class title, date, and the assignment number.

• Include a table of contents and a reference section. Number your pages in the footer along with the date. Include a header starting on page 2 with the Course and assignment number.
• Write the problem number and the problem title as a level one heading (Example ‐ A.1.1: Chapter 2, Problem 2.1, Check the Completed Questionnaires) and then provide yourresponse.
• Use level two headings with short titles for multi part questions (Example ‐ A1.1.a, Short Title, A1.1.b, Short Title II, etc.)
• Use appropriate level headings for key elements of your discussion such as Research Questions, Hypotheses, Descriptive Statistics, Assumptions & Conditions, Interpretation, Results, and others. Your goal is to make your analysis easy to follow and logical.
• Ensure that all tables and graphs are legible and include a figure number.
• Carefully review your document prior to submission for formatting, flow, and readability. Keep in mind that running the statistical tests is only the first half of the challenge; you must be able to clearly communicate your findings to the reader!
• . Cut and paste your outputs directly into your document and refer to them in your interpretation.
• At least 3 references for each assignments

Assignment 6

A6.1: Chapter 9, Problem 9.1, Scatterplots to Check the Assumption of Linearity. Write a short narrative of your process and interpretation of your findings. , Cut and paste the Scatterplots with Regression Lines from Output 9.1a and 9.1b directly into your document and refer to them in your interpretation.

A6.2: Chapter 9, Problem 9.2, Bivariate Pearson and Spearman Correlations. Write a short narrative of your process, an interpretation of your findings, and write your results. Cut and paste the Descriptive Statistics, Correlations, and Nonparametric Correlations tables directly into your document and refer to them in your interpretation.

A6.3: Chapter 9, Problem 9.3, Correlation Matrix for Several Variables. Write a short narrative of your process, an interpretation of your findings, and write your results to include tables. Cut and paste the Descriptive Statistics and Correlations tables directly into your document and refer to them in your interpretation.

A6.4: Chapter 9, Problem 9.4, Bivariate or Simple Linear Regression. Write a short narrative of your process, an interpretation of your findings, and write your results. Cut and paste the Model Summary, Variables Entered/Removed, ANOVA, and Coefficients tables directly into your document and refer to them in your interpretation.

A6.5: Chapter 9, Problem 9.5, Multiple Regression. Write a short narrative of your process, an interpretation of your findings, and write your results to include tables. Cut and paste the Descriptive Statistics, Correlations, Variables Entered/Removed, Model Summary, ANOVA, and Coefficients tables directly into your document and refer to them in your interpretation.

A6.6, Application Problem ‐ Correlation and Regression. Using the “college student data.sav” file, do the following problems. Write a short narrative of your process, an interpretation of your findings, and write your results to include tables. Cut and paste your outputs directly into your document and refer to them in your interpretation.

• Write a research question and a null hypothesis exploring the relationship between student’s height and parent’s height. Conduct a correlation analysis to test the relationship including a scatterplot. Include Descriptive Statistics, Correlations, and Nonparametric Correlations tables and refer to them in your interpretation. Prior to running the analysis, discuss how the data meets the assumptions and conditions for the tests you are going to conduct. Support your assertion with the appropriate descriptive statistics.
• Write a research questions and a null hypothesis exploring the relationship between student gender, parent’s height, and student’s height to see if student’s height can be predicted. Before beginning the

test, recode gender (1 = male, 2 = female) to “Male” (1 = male, 0 = not male).

Explain why recoding gender “Male” was necessary to run this test. Conduct a regression analysis to test the relationship. Include Descriptive Statistics, Correlations, Variables Entered/Removed, Model Summary, ANOVA, and Coefficients tables and refer to them in your interpretation. Prior to running the analysis, discuss how the data meets the assumptions and conditions for the tests you are going to conduct. Support your assertion with the appropriate descriptive statistics.