Researchers use data analytics to investigate various factors and their impact o

Researchers use data analytics to investigate various factors and their impact on situations and outcomes. When dealing with data that contains more than two variables, multivariate analysis is used to gain a deeper understanding of data in relation to specific scenarios, such as the possibility of a correlation between “weekly hours of exercise” and “cholesterol level.” This can help lead to an understanding of certain outcomes and their triggers, which in turn can lead to informed public health predictions and policy decisions.
In this third part of the Scholar Practitioner Project (SPP), you will develop an interpretation of a multivariate analysis based on your selected data set, your prepared database, and SPSS calculations. You will make sense of this interpretation and communicate it to users by using tables and/or graphs.
SCHOLAR PRACTITIONER PROJECT – MULTIVARIATE ANALYSIS
For each of the research questions that you developed, provide interpretation of your multivariate inferential statistical analyses (using linear and/or logistic regression) SPSS outputs. Include diagnostics in your submission. Be sure to address the following:
State the research question(s).
State the null and alternative hypotheses.
Perform the diagnostics and record the results.
Summarize the numerical results with multivariate inferential analysis (using linear and/or logistic regression) tables or graphs, including your interpretation. Follow APA rules for tables and graphs.
Explain how your results could positively impact social change (use outside sources as needed in your explanation).
PUBH_8546_Module5_SPP_Rubric
PUBH_8546_Module5_SPP_Rubric
CriteriaRatingsPts
This criterion is linked to a Learning OutcomeResearch Question, Null and Alternative Hypotheses: For each research question, state the research question, null hypothesis, and alternative hypothesis. Perform the diagnostics and record the results.
20 to >17.0 ptsOutstanding
Fully developed and supported, insightful, credible, and scholarly statement of each research question, null hypothesis, and alternative hypothesis, with appropriate diagnostics performed and results appropriately recorded.
17 to >15.0 ptsVery Good
Thorough, well-organized, and supported statement of each research question, null hypothesis, and alternative hypothesis, with appropriate diagnostics performed and results appropriately recorded.
15 to >13.0 ptsMeets Expectations
Adequate statement of each research question, null hypothesis, and alternative hypothesis, with appropriate diagnostics performed and results appropriately recorded.
13 to >0 ptsDoes Not Meet Expectations
Missing, unoriginal, or does not adequately state each research question, null hypothesis, and alternative hypothesis, or does not appropriately perform the diagnostics and appropriately record the results.
20 pts
This criterion is linked to a Learning OutcomeMultivariate inferential analysis: Summarize the numerical results with multivariate inferential analysis (using linear and/or logistic regression) tables or graphs, including interpretation. Follow APA rules for tables and graphs.
20 to >17.0 ptsOutstanding
Fully developed and supported, insightful, credible, and scholarly summary of the numerical results with multivariate inferential analysis (using linear and/or logistic regression) tables or graphs, including interpretation, following APA rules for tables and graphs.
17 to >15.0 ptsVery Good
Thorough, well-organized, and supported summary of the numerical results with multivariate inferential analysis (using linear and/or logistic regression) tables or graphs, including interpretation, following APA rules for tables and graphs.
15 to >13.0 ptsMeets Expectations
Adequate summary of the numerical results with multivariate inferential analysis (using linear and/or logistic regression) tables or graphs, including interpretation, following APA rules for tables and graphs.
13 to >0 ptsDoes Not Meet Expectations
Missing, unoriginal, or does not adequately summarize the numerical results with multivariate inferential analysis (using linear and/or logistic regression) tables or graphs, including interpretation, or does not follow APA rules for tables and graphs.
20 pts
This criterion is linked to a Learning OutcomeSocial Change: Explain how the results could positively impact social change.
20 to >17.0 ptsOutstanding
Fully developed and supported, insightful, credible, and scholarly explanation of how the results could positively impact social change.
17 to >15.0 ptsVery Good
Thorough, well-organized, and supported explanation of how the results could positively impact social change.
15 to >13.0 ptsMeets Expectations
Adequate explanation of how the results could positively impact social change.
13 to >0 ptsDoes Not Meet Expectations
Missing, unoriginal, or does not adequately explain how the results could positively impact social change.
20 pts
This criterion is linked to a Learning OutcomeResources: Support your response with at least five peer-reviewed articles/scholarly resources (less than 5 years old) and properly cite/reference using APA 7.
20 to >17.0 ptsOutstanding
Fully developed and supported, insightful, credible, and scholarly support for responses with at least five peer-reviewed articles/scholarly resources (less than 5 years old) properly cited in APA 7. No referencing/citing errors.
17 to >15.0 ptsVery Good
Thorough, well organized, and supported support for responses with at least five peer-reviewed articles/scholarly resources (less than 5 years old) properly cited in APA 7. Only one minor referencing/citing error.
15 to >13.0 ptsMeets Expectations
Adequate support for responses with at least five peer-reviewed articles/scholarly resources (less than 5 years old) properly cited in APA 7. Two to three minor referencing/citing errors.
13 to >0 ptsDoes Not Meet Expectations
Missing, unoriginal, or does not adequately support your responses with at least at least five peer-reviewed articles/scholarly resources (less than 5 years old) or properly cite/reference using APA 7.
20 pts
This criterion is linked to a Learning OutcomeWritten Communication: Extent to which writing is professional, appropriate, clear, properly formatted, grammatically and structurally correct, synthesized, supported, and scholarly.
20 to >17.0 ptsOutstanding
Writing is fully developed, exceptionally well organized, synthesized, supported, scholarly, and free of writing errors. Concepts are connected throughout paper with appropriate transitions and multiple appropriate resources and examples.
17 to >15.0 ptsVery Good
Writing is generally thorough and grammatically correct, with proper formatting and minimal concerns. Synthesis is demonstrated and ideas are supported without reliance on quoting.
15 to >13.0 ptsMeets Expectations
Writing adequately meets expectations for writing and synthesis but with infrequent and minor issues.
13 to >0 ptsDoes Not Meet Expectations
Writing does not meet basic expectations (e.g., clarity, tone, organization, grammar, spelling, punctuation, source citation, references, title page, synthesis of source material, insufficient originality, etc.).
20 pts
Total Points: 1001
. Some of you have opted to use a test other than linear or logistic regression. Do not do this. Use linear or logistic regression. This is the focus of this class.
2. Use bivariate analysis like correlation or chi-squared to determine what variables belong in your regression model; Do not use it as your main analysis.
3. Make sure you are meeting the model assumptions. The logistic or linear regression is based on the type of variables you have. (See previous announcements).
4. Be sure that you use only peer reviewed references. This means journal articles. Do not use websites to substantiate your work.
5. Format your references, tables, and graphs and interpretations (https://www.scribbr.com/apa-style/numbers-and-statistics/properly in APA style.
6. Remember that with categorical variables you cannot run mean, median, sd, ranges. You can only run frequencies.
7. Be sure that you proofread.