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. a. 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. b. 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. 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.
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