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QUANTITATIVE ANALYSIS: CORRELATION AND REGRESSION SPSS Questions Chapter 8 Using the CollegeStudentData.sav set (see Appendix A on how to retrieve it), do the following problems. Print your outputs af
QUANTITATIVE ANALYSIS: CORRELATION AND REGRESSIONSPSS QuestionsChapter 8Using the CollegeStudentData.sav set (see Appendix A on how to retrieve it), do the followingproblems. Print your outputs after typing your interpretations on them. Please circle the keyparts of the output that you discuss.8.1 What is the correlation between student’s height and parent’s height? Also produce ascatterplot. Interpret the results, including statistical significance, direction, and effect size.8.2 Write a question that can be answered via correlational analysis with two approximatelynormal or scale variables. Run the appropriate statistics to answer the question. Interpret theresults.8.3 Make a correlation matrix using at least four appropriate variables. Identify, using thevariable names, the two strongest and two weakest correlations. What were the r and p valuesfor each correlation?8.4 Is there a combination of gender at birth and same-sex parent’s height that significantlypredicts student’s height?Make Sure to:1. Attach your word document for review and grading. Other file formats are notaccepted and will not be graded. Use the following filename format:LastName_BUSI820_AssignmentX.docx2. Include an APA title block with your name, class title, date, and the assignment number.3. Include a table of contents and a reference section. Number your pages in the footeralong with the date. Include a header starting on page 2 with the Course andassignment number.4. Write the problem number and the problem title as a level one heading (Example ‐A.1.1: Chapter 2, Problem 2.1, and then provide your response.5. Use level two headings with short titles for multi part questions (Example ‐ A1.1.a,Short Title, A1.1.b, Short Title II, etc.)6. Use appropriate level headings for key elements of your discussion such as ResearchQuestions, Hypotheses, Descriptive Statistics, Assumptions & Conditions,Interpretation, Results, and others. Your goal is to make your analysis easy to followand logical.7. Ensure that all tables and graphs are legible and include a figure number.8. Carefully review your document prior to submission for formatting, flow, andreadability. Keep in mind that running the statistical tests is only the first half of thechallenge; you must be able to clearly communicate your findings to the reader.
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** *********** Between Student’s ****** *** ********** ********* ****** association ******* ********* ****** ******** *** ******** height (pheight) was ********* using * Pearson *********** coefficient presuming **** given *** context ** *** ******* ******* refers ** *** ****** ** *** ******** ****** ******** ***** (N * ** **** ** ******* values *** ***** variables) **** **** for the ******** ** illustrate *** link * *********** *** created **** ****** ******* ***** a ******** ****** ***** line Taller parents **** ********** **** taller ******** *** ******* ******** **** ******* ** an *************************** ****** and ********* ****** **** * positive *** *********** ********** (r * 0842) meaning that students' ****** ***** to **** as ******** ****** **** ***** **** *** *********** is ************* *********** (p < ***** ** ** unlikely to ** the ****** ** ****** * = 0842 ** a ***** ****** size that ******** ****** **** ** the ****** ******** **** * ***** **** ****** ******* ****** an ****** trend *** *********** ******** * ******** direction *** ******* ******** ********** * ****** ******* influence ** height82 Correlational ******** with Two Scale ***************** and EvaluationTwo ******* scaled ********* (hrsstudy and currgpa) from *** dataset **** used ** ********* * Pearson correlation ** ******* *** ******** question ******** ******** ** * 49 *** missing ***** ** ****** ******** ** currgpa) ****** ** *** ***** *** *** ******************* ***** ***** ******** an ******** of *** ******* *********** ******** **** * = **** *** * = **** *** ********** *** *** ************* significantVariable ********************* * ************************************ ** * minor ******** *** ****** study ***** to be ****** to ****** *** ** ********* ** *** positive *** **** correlation ** * ***** between weekly study ***** and ******* *** ***** ******* ** ** ** ******** ****** link ** **** sample ****** as *** relationship ** *** ************* *********** ** * ***** **** ****** 12% ** *** ****** ******** *** * ***** ** ********* by the **** effect **** ** * ***** ********** **** other ************** ***** ********** ** ***** ***************** **** * ******* ****** ** *** **** study hours ******* *********** Matrix **** **** ** **** ******************** and EvaluationSix ***** ****************** ******* ***** ****** ***** watching *** ******** (hours ***** ********* currgpa (current **** *** hrswork (hours ***** *************** used ** ****** * *********** ****** ******** ***** ** * 50 after accounting *** any missing ******* **** ******** ** *** ******** *** ***** pair p-values and Pearson ************ *** **** ********** ******* & ******* **************** ****** ******* *** ******** *** *********** matrix ****** *** ******* ** * 0841 * **** ***** *** hours ****** and ***** ******* ** * ***** * **** ***** had *** *** **** *********** ************ ******** ******** ** ****** and ******* ** * -0094 p = ***** *** pheight and hrswork ** = ***** p * 0634) had the *** ******* ************* (lowest absolute ********* *********** Matrix ** ************************************************************************************************************************************************************************************************************************************************************************* *** ********************************************************************************************************************************************* 0001Hrsstudy001400080011-04360131Currgpa0107032200890436-0034Hrswork05210634< ************************************** ************* ******* *** variables *** ******** by the correlation matrix ****** *** ******* have *** **** significant ********** (r * 0841 * **** 0001) suggesting * strong ******** ************ **** ** probably ****** ** hereditary ******* *** ************ ******* ******* and hrstv ** *** ****** ********* ** * ***** * **** ***** ********** * ******** *********** relationship in which fewer ** hours *** ********** **** **** **** ***** ******* *** ******* **** the poorest association (r * -0070 * = ***** ********** almost no relationship ****** and ***** ****** had *** ************** *********** (r * ***** p * ***** which ** ********* ************* ***** ******* demonstrate *** ************ of physical *************** from behavioral ******* **** ** ***** *** **** ******** Predicting Student’s ****** **** ****** *** Same-Sex Parent’s ************** Regression Summary: ********** ************************** ******* Errort-valuep-value95% ** ******** CI UpperConstant3548557006226< ************************************************************************ **************************** ** demonstrated ** *** *********** ******* ***** **** 47) * **** * **** ***** explaining 748% ** *** variance (R2 * 0748) *** height ** * ******* ** ******** ********* by *** *********** ** gender at birth and *** ****** ** a ******** ****** Higher parent height ******** ******** higher ******* ****** *** = **** p **** ***** *** ***** male ********** predicts ****** height (β = 2491 * * 0009) **** ******* **** biological ******* **** ** sex *********** *** ******** *** ********* ** *********** ****** *********** ***** ****** ************************* * ***** ******* * ****** *** **** ********** ** step ** ***** * ****** ***** *** ********* ***** *** RoutledgeTabachnick * G & ****** * S ****** ***** multivariate ********** **** ed) *******
