Correlation and Bivariate Regression (SPSS)

To prepare for this Discussion:Construct a research question using the General Social Survey dataset, which can be answered by a Pearson correlation and bivariate regression.By Day 3Use SPSS to answer the research question. Post your response to the following:What is your research question?What is the null hypothesis for your question?What research design would align with this question?What dependent variable was used and how is it measured?What independent variable is used and how is it measured?If you found significance, what is the strength of the effect?Explain your results for a lay audience; explain the answer to your research question.Be sure to support your Main Post and Response Post with reference to the week’s Learning Resources and other scholarly evidence in APA Style.Professor’s Note on how to complete the assignment:”Week 8 Discussion: How To Complete The Discussion RequirementReview the Week 8 Course MaterialsUse the General Social Survey (GSS) dataset for this DiscussionIdentify the independent variable (IV) and its Level of Measurement. The IV must be interval or ratio).Identify the dependent variable (DV) and its Level of Measurement. The DV must be interval or ratio.Write a research question for Pearson correlation/and bivariate regression. Use this format: – What is the relationship between (state the DV) and (state the IV)?Write the null hypothesis. Use this format: -There is no relationship between (state the DV) and (state the IV).State the research design.Use SPSS to answer the research question. Here’s how:-Open the GSS data set, select Analyze, select Correlate, Select Bivariate, drag your IV and DV into the Variables box, and click OK.-Review the Sig. value in the SPSS Output under Correlations and decide to reject or fail to reject the null hypothesis.-If you reject the null and determine that the ANOVA is statistically significant, report the report and explain the Pearson Correlation and calculate, report, and explain the effect size.-The effect size is the square of the Pearson Correlation and is also known as the Coefficient of Determination. You must calculate this value and it must be between -1 and +1.”If you fail to reject the null and find that the Pearson Correlation is not statistically significant, then there is no need to calculate, report, or explain the effect size.

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