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IMPORTANT NOTE REGARDING WORD LIMIT REQUIREMENTS:Please note that each and every assignment has its own word limit. The purpose of this assignment is to apply your understanding of simple and multiple linear regression.For this assignment, use the Example Dataset to complete a simple linear regression using SPSS. Select one dependent variable, one primary independent variable, and one potential confounding variable. You will need to recode string variables into numeric variables to use them in the regression analysis. Prepare a Word document that includes all SPSS outputs.Based on the results, create a second Word document and answer the following questions in 500-750 words.State your research question and hypotheses.Run the regression again without the potential confounding variable and discuss the impact on the coefficient of the primary independent variable. Did it change? If so, to what extent did it change? Based on this, do you think the added variable confounds the association between the independent and dependent variables?Export both regression output tables as part of the Word document containing the SPSS outputs.Provide your regression equation based on the results of the full regression model.Interpret the results by (a) stating the reason the study or test was done; (b) presenting the main results, including coefficients on the main independent variable and significance levels; (c) explaining what the results mean; and (d) making suggestions for future research. Submit both Word documents to the instructor. General RequirementsYou are required to cite at least FIVE sources to complete this assignment. Sources must be published within the last 5 years and appropriate for the discussion question criteria and public health content.Prepare this assignment according to the guidelines found in the APA Style Guide. An abstract is not required.While APA style is required, solid academic writing is expected as well, and documentation of sources should be presented using APA formatting guidelines.This assignment uses a rubric. Please review the rubric prior to beginning the assignment to become familiar with the expectations for successful completion. PLEASE make sure APA citation and permalink for articles are complete and correct. PLEASE add the links/sites below to the reference list if you use any of these readings and make sure everything is in proper APA format.https://apastyle.apa.org/learn/quick-guide-on-refe... Read Chapter 14 in Using and Interpreting Statistics: A Practical Text for the Behavioral, Social, and Health Sciences.URL: http://www.gcumedia.com/digital-resources/macmillan-learning/2016/using-and-interpreting-statistics_a-practical-text-for-the-behavioral-social-and-health-sciences_ebook_3e.php View the Linear Correlation tutorial in the SPSS Tutorials media.URL: http://lc.gcumedia.com/psy380/spss-tutorials/v1.1/ View the following calculations in The Visual Learner: Statistics media.Coefficient of VariationLinear RegressionLinear CorrelationNon-Parametric Test Chi-SquareURL: http://lc.gcumedia.com/hlt362v/the-visual-learner/the-visual-learner-v2.1.html Read Regression Modelling and Other Methods to Control Confounding, by McNamee, from Occupational & Environmental Medicine (2005).URL: http://oem.bmj.com/content/62/7/500Read How to Control Confounding Effects by Statistical Analysis, by Pourhoseingholi, Baghestani, and Vahedi, from Gastroenterology and Hepatology From Bed to Bench (2012).URL: https://www-ncbi-nlm-nih-gov.lopes.idm.oclc.org/pmc/articles/PMC4017459/ MUST have 500 to 750 WORDS and at least 5 citations with the page numbers and 5 references in APA format.(The List of References should not be older than 2016 and should not be included in the word count.) Be sure to support your postings and responses with specific references to the Learning Resources.It is important that you cover all the topics identified in the assignment. Covering the topic does not mean mentioning the topic BUT presenting an explanation from the context of ethics and the readings for this class I am a stickler for good organization in everything. I do not want to have to dig for your answers. For instance, if an assignment asks you to provide three examples of something, I suggest that you number them 1-3 so I can find them easily. I also expect that when you submit something as a narrative, you pay attention to how you organize your thoughts: use paragraphs with a topic sentence and supporting sentences; and change paragraphs whenever you introduce a new idea. Also, if there are multiple parts to an assignment, use sub-heads within the paper to organize them. To get maximum points you need to follow the requirements listed for this assignments 1) look at the word/page limits 2) review and follow APA rules 3) create subheadings to identify the key sections you are presenting and 4) Free from typographical and sentence construction errors.REMEMBER IN APA FORMAT JOURNAL TITLES AND VOLUME NUMBERS ARE ITALICIZED. pub_550_week_6_application_of_multiple_regression_rubric_guide.xlsx pub_550__week_6_rs_example_dataset_application_of_multiple_regression_.xlsx Unformatted Attachment Preview Course Code PUB-550 Class Code PUB-550-O500 Criteria Content Percentage 100.0\% SPSS Outputs 20.0\% Research Question and Hypothesis 10.0\% Simple Linear Regression Analysis 25.0\% Regression Equation 10.0\% Interpretation of Results (a) stating the reason the study or test was done, (b) presenting the main results including coefficients on the main independent variable and significance levels, (c) explaining what the results mean, and (d) making suggestions for future research 30.0\% Mechanics of Writing (includes spelling, punctuation, grammar, language use) 5.0\% Total Weightage 100\% Assignment Title Application of Multiple Regression Unsatisfactory (0.00\%) SPSS output tables illustrating the use of one dependent variable, one primary independent variable, and one confounding variable to complete a linear regression are not included. Statement of research question and hypotheses is not included. Discussion of the simple linear regression conducted without the potential confounding variable; the impact on the coefficient of the primary independent variable; changes; and how the variable confounds the association between the independent and dependent variables is not included. Regression equation based on the results of the full regression model is not included. Interpretation of results, including steps a-d, is not included. Surface errors are pervasive enough that they impede communication of meaning. Inappropriate word choice or sentence construction is used. Total Points 70.0 Less than Satisfactory (74.00\%) SPSS output tables illustrating the use of one dependent variable, one primary independent variable, and one confounding variable to complete a linear regression are incomplete or incorrect. Statement of research question and hypotheses is incomplete or incorrect. Discussion of the simple linear regression conducted without the potential confounding variable; the impact on the coefficient of the primary independent variable; changes; and how the variable confounds the association between the independent and dependent variables is incomplete or incorrect. Regression equation based on the results of the full regression model is incomplete or incorrect. Interpretation of results, including steps a-d, is incomplete or incorrect. Frequent and repetitive mechanical errors distract the reader. Inconsistencies in language choice (register) or word choice are present. Sentence structure is correct but not varied. Satisfactory (79.00\%) SPSS output tables illustrating the use of one dependent variable, one primary independent variable, and one confounding variable to complete a linear regression are partially complete and correct. Statement of research question and hypotheses is partially complete and correct. Discussion of the simple linear regression conducted without the potential confounding variable; the impact on the coefficient of the primary independent variable; changes; and how the variable confounds the association between the independent and dependent variables is included but lacks explanation and supporting details. Regression equation based on the results of the full regression model is partially complete and correct. Interpretation of results, including steps a-d, is included but lacks explanation and relevant details. Some mechanical errors or typos are present, but they are not overly distracting to the reader. Correct and varied sentence structure and audience-appropriate language are employed. Good (87.00\%) SPSS output tables illustrating the use of one dependent variable, one primary independent variable, and one confounding variable to complete a linear regression are mostly complete and correct. Statement of research question and hypotheses is mostly complete and correct. Discussion of the simple linear regression conducted without the potential confounding variable; the impact on the coefficient of the primary independent variable; changes; and how the variable confounds the association between the independent and dependent variables is complete and includes explanation and supporting details. Regression equation based on the results of the full regression model is mostly complete and correct. Interpretation of results, including steps a-d, is complete and includes explanation and relevant details. Prose is largely free of mechanical errors, although a few may be present. The writer uses a variety of effective sentence structures and figures of speech. Excellent (100.00\%) SPSS output tables illustrating the use of one dependent variable, one primary independent variable, and one confounding variable to complete a linear regression are complete and correct. Statement of research question and hypotheses is complete and correct. Discussion of the simple linear regression conducted without the potential confounding variable; the impact on the coefficient of the primary independent variable; changes; and how the variable confounds the association between the independent and dependent variables is extremely thorough and includes substantial explanation and supporting details. Regression equation based on the results of the full regression model is complete and correct. Interpretation of results, including an explanation of the regression equation and steps a-d, is extremely thorough with substantial explanation and relevant details. Writer is clearly in command of standard, written, academic English. Comments Points Earned A local community organization was interested in learning about general health behaviors in the area and the relationships between health behaviors and environmental and social determinants. They decided to conduct a brief survey based on a convenient sample of people visiting the local shopping mall. They offered a $5 incentive for completing the survey. The Topic 1 Example dataset includes 30 observations from this survey. Use this data to complete the relevant assignments in this course. Education Level 1 2 3 Less than High School Graduated High School Graduated College Annual Income = US Dollars ehaviors in the area and the ts. They decided to conduct a all. They offered a $5 incentive from this survey. Use this data to ID 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 Sex Female Male Female Male Female Female Female Male Female Male Female Male Female Male Male Male Female Male Male Female Female Female Male Male Female Male Female Female Male Male Smoker No No Yes No Yes Yes No Yes Yes No No No Yes No No No No Yes Yes No Yes No No No No Yes Yes No No Yes Education_Level*** 2 2 3 1 1 2 3 1 2 2 3 1 1 3 2 1 2 3 2 1 2 3 2 1 1 3 3 1 3 3 Minutes_Exercise 90 50 65 20 50 25 110 50 40 80 120 80 60 150 75 80 110 80 100 0 50 200 60 65 40 65 70 45 75 50 Age 45 58 31 54 30 18 39 37 44 24 42 50 20 35 61 59 36 35 29 32 26 42 52 49 21 48 40 53 46 42 Employed Yes No Yes No Yes No Yes Yes Yes No Yes Yes No Yes Yes No Yes Yes No No No Yes No No No Yes Yes No Yes Yes Annual_Income*Neighborhood 51000 B 23000 C 35000 B 10000 C 28000 B 5000 C 46000 A 36000 B 51000 C 12000 A 78000 A 34000 D 15000 B 28000 B 28000 A 24000 B 55000 D 62000 B 32000 D 7000 C 17000 B 64000 D 5000 A 14000 D 20000 C 72000 A 85000 A 15000 B 64000 C 27000 B ... 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