Please review the accuracy for WK9-DQ-RSCH-8210

DQ = Use 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? What other variables were added to the multiple regression models as controls? What is the justification for adding the variables? If you found significance, what is the strength of the effect? Explain your results for a lay audience, explain what 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. What is the research design used by the authors? Why did the authors use correlation or bivariate regression? Do you think it’s the most appropriate choice? Why or why not? Did the authors display the data? Do the results stand alone? Why or why not? Did the authors report effect size? If yes, is this meaningful? 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. Don’t talk about cause and affect with regression. This is a correlational design, so you cannot show that the IV affects the DV. You can only talk about relationships where the IV predicts the DV. You need to have at least two IVs for regression. Only use one DV. With your RQ, it’s helpful to write it like this: RQ1: Is the IV a significant predictor of DV when controlling for other variables? Of course, you need to list what the IVs and DV are. This was just an example. You also need to have an RQ for each predictor. When conducting regression, you want your hypotheses to address each variable when controlling for other variables. So if you have two IVs, this is how you might do it: Ho1: Age is not a significant predictor of Income when controlling for all other variables Ho2: SES is not a significant predictor of Income when controlling for all other variables etc. The alternative hypothesis should simply be the opposite of the Ho. For example, if you say: Ho: Highest year of education is not a significant predictor of SES scores when controlling for other variables. Then you would have the following alternative hypothesis: Ha: Highest year of education is a significant predictor of SES scores when controlling for other variables. Regression results are often best presented in a table. APA doesn’t say much about how to report regression results in the text, but if you would like to report the regression in the text of your Results section, you should at least present the unstandardized or standardized slope (beta), whichever is more interpretable given the data, along with the t-test and the corresponding significance level. (Degrees of freedom for the t-test is N-k-1 where k equals the number of predictor variables.) It is also customary to report the percentage of variance explained along with the corresponding F test. Examples: Social support significantly predicted depression scores, b = -.34, t(225) = 6.53, p < .001. Social support also explained a significant proportion of variance in depression scores, R2 = .12, F(1, 225) = 42.64, p < .001. http://my.ilstu.edu/~jhkahn/apastats.html The design for regression analyses is a correlational design. I hope this helps! 🙂

Dee Jay38 minutes ago

Whether in a scholarly or practitioner setting, good research and data analysis should have the benefit of peer feedback. For this Discussion, you will post your response to the hypothesis test, along with the results. Be sure and remember that the goal is to obtain constructive feedback to improve the research and its interpretation, so please view this as an opportunity to learn from one another. To prepare for this Discussion: Review this week’s Learning Resources and media program related to multiple regression. Create a research question using the General Social Survey that can be answered by multiple regression.

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