SO 510: Final Project Guidelines and Rubric Overview The final project for this course is the creation of a research paper. You will select a specific problem you see in the workplace (or, if you have limited work experience, that you would find it valuable to solve in your home life) and then identify what you wish to study. You must apply the theories and concepts from the course to interpret and formulate your hypotheses. Be sure to identify why the answer/solution matters. Once you have your hypotheses, go through the scientific method and statistical process to sample and answer the question. Be sure that you justify the statistical test that you use and either reject or fail to reject the null hypothesis based on the data. Your conclusion should be entirely data driven, with the implications clear. The project is divided into three milestones, which will be submitted at various points throughout the course to scaffold learning and ensure quality final submissions. These milestones will be submitted in Modules Three, Five, and Seven. The final submission will occur in Module Nine. Milestone 1: The focus is on selection of a topic and identification of the tools used to solve the problem and/or test the hypothesis. If the topic is not appropriate or needs to be streamlined, the instructor will proved feedback to assure the topic can become a viable final project. Milestone 2: The emphasis is on the raw data and data analysis strategy that will be used to test your hypothesis and/or solve your problem. In this milestone your instructor will provide feedback to assure the raw data collected is appropriate for the topic and the data analysis strategy will support solving the problem or testing the hypothesis. Milestone 3: This is a draft of your final project. The instructor will provide feedback identifying the actions necessary to fulfill the requirements for the final project due in Module 9. Outcomes In this assignment, you will demonstrate your mastery of the following course outcomes: Provide students with a basic understanding of several quantitative techniques that are used extensively for decision making in business Enable students to recognize problem areas in their fields of professional responsibilities and to apply the appropriate quantitative methods for obtaining rational solutions Increase the student's effectiveness in communicating with other specialists in the firm such as industrial engineers, production managers, operations researchers, statisticians, and other problem-solving and decision-making persons Enable students to use the power of the spreadsheets and statistical software in the application of the quantitative techniques Prompt Statistics is the study that pertains to the collection, analysis, explanation or interpretation, and presentation of data. Interpretation of statistical information often involves the development of a null hypothesisthat whatever is proposed as a cause has no effect on the variable being measured. Specifically, the following critical elements must be addressed: 1. Statistical Argument: Propose an argument that answers the prompt. Include a strong thesis statement connected to datadriven evidence. a. Topic Selection: Select an appropriate topic and provide a detailed explanation of the significance. b. Citations: Paraphrase and/or integrate quotes effectively. 2. Data Collection: Once you finalize your research question, compile your research and collect raw data. a. Organization: Include a clearly stated thesis and a well-organized body section of your paper. 3. Statistical Process: Using your knowledge of the scientific method and statistical process to analyze the data: a. Descriptive Statistics: Summarize the population data by describing what was observed in the sample set numerically or graphically. b. Inferential Statistics: Use patterns in the sample data to draw inferences about the population represented, accounting for randomness. These inferences may take the form of hypothesis testing (e.g., answering yes/no questions about the data), estimation (estimating numerical characteristics of the data), correlation (describing associations within the data), and modeling relationships within the data. c. Null Hypothesis: Refer to a general or default positionthat there is no relationship between two measured phenomena. Rejecting or disproving the null hypothesis is concluding that there are grounds for believing that there is a relationship between two phenomena or that a potential treatment has a measurable effect. 4. Primary-Source Analysis: Select sources in support of your thesis statement. Critically examine the sources in context of your paper topic. Remember that this is not based on opinion, but rather based on analysis of the statistical data. The source methodology supports your thesis statement. Milestones Milestone One: Topic Selection In Module Three, you will submit a 2-3-page paper summarizing your topic selection. Why did you select this topic? What is the significance? Which statistical method(s) will be used? The feedback provided by the instructor should be applied to your final research paper. This milestone is graded with the Milestone One Rubric. Milestone Two: Collection of Data In Module Five, you will submit your raw data. You do not need your analysis to have been completed yet, but you do need your data. Make sure to present data in a well-organized spreadsheet. The feedback provided by the instructor should be applied to your final research paper. This milestone is graded with the Milestone Two Rubric. Milestone Three: Rough Draft In Module Seven, you will submit your rough draft of your data, analysis, and conclusions. List any questions or concerns you may have. In this draft, offer any analysis tools that you see as appropriate. The instructor will provide feedback. Apply this feedback to your final research paper. This milestone is graded with the Final Product Rubric (below). Final Submission: Research Paper In Module Nine, you will submit your final research paper. It should be a complete, polished artifact containing all of the critical elements of the final product. It should reflect the incorporation of feedback gained throughout the course. This is graded with the Final Product Rubric (below). Deliverable Milestones Mileston Deliverables e 1 Topic Selection 2 Collection of Data 3 Rough Draft Final Submission: Research Paper Module Due Three Five Seven Nine Grading Graded separately; Milestone One Rubric Graded separately; Milestone Two Rubric Graded separately; Final Product Rubric Graded separately; Final Product Rubric Final Product Rubric Format: Your research paper should be 10 to 15 pages, plus a title page and references page. The paper should have double spacing, 12-point Times New Roman font, 1-inch margins, and APA citation style. The title page and references page will not be considered as part of the page count for this assignment. Instructor Feedback: Students can find their feedback in the Grade Center or Turnitin. Critical Elements Exemplary (100%) Topic Selection Meets \"Proficient\" criteria and provides a substantially detailed rationale of topic's significance Meets \"Proficient\" criteria, and thesis exhibits strength and insight Meets \"Proficient\" criteria and supports explanation with relevant examples from research Meets \"Proficient\" criteria, and explanation is comprehensive Clearly identifies the topic and provides sufficient rationale of topic's significance Needs Improvement (70%) Does not clearly identify the topic; rationale is insufficient Proposes a clear and complete thesis statement Clearly and sufficiently explains statistical process Inferential Statistics Meets \"Proficient\" criteria, and explanation is comprehensive Clearly and sufficiently explains how data relates to inferential statistics Modeling Relationships Within the Data Meets \"Proficient\" criteria, and the modeling relationships chosen are appropriate, well justified, and substantially supported Clearly illustrates modeling relationships within the data, with sufficient support Thesis Data Collection Descriptive Statistics Proficient (90%) Clearly and sufficiently explains how data relates to descriptive statistics Not Evident (0%) Value Does not identify the topic or explain the rationale 10 Thesis is unclear and/or incomplete Does not propose thesis statement 10 Explanation of statistical process is unclear and/or insufficient Explanation of relationship between data and descriptive statistics is unclear or insufficient Explanation of relationship between data and inferential statistics is unclear or insufficient Modeling relationships are insufficient, inaccurate, and/or unsupported Does not explain the statistical process 10 Does not explain how the data relates to descriptive statistics 5 Does not explain how the data relates to inferential statistics 5 Submission has no documentation of modeling relationships 10 Null Hypothesis Meets \"Proficient\" criteria, and explanation is insightful and thorough Clearly and accurately explains why the null hypothesis is rejected or not rejected Meets \"Proficient\" criteria, and interpretation draws astute conclusions that go beyond existing research Provides a valid and logical interpretation of statistical thought substantiated by research Primary Source Analysis Meets \"Proficient\" criteria and includes clear supporting details for the statistical context Data Analysis Meets \"Proficient\" criteria and alternative possibilities for the analysis tools chosen Sufficiently identifies source methodology and clearly relates each to specific statistical context in which it was written Tools and the analysis plan fully defined and supported Articulation of Response Submission is free of errors related to citations, grammar, spelling, syntax, and organization and is presented in a professional and easyto-read format Statistical Arguments Earned Total Comments: Submission has no major errors related to citations, grammar, spelling, syntax, or organization; quotes and paraphrases are effectively integrated Explanation of why null hypothesis is rejected or not rejected is unclear, inaccurate, and/or incomplete Interpretation of statistical thought is invalid and/or illogical; conclusions are not substantiated by research Analysis of source methodology is insufficient and/or unclear Does not explain why the null hypothesis is rejected or not rejected 10 Does not provide an interpretation of statistical thought 10 Does not identify source methodology 10 Defined tools but it is not logical or appropriate for the plan Does not identify tools or plan 10 Submission has major errors related to citations, grammar, spelling, syntax, or organization that negatively impact readability and articulation of main ideas; quotes and paraphrases are awkwardly integrated 100% Submission has critical errors related to citations, grammar, spelling, syntax, or organization that prevent understanding of ideas 10