Final Project
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qso_510_final_project_document_1.docx
QSO 510: Final Project Guidelines and Grading Guide
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 two 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 and Seven. The final submission will occur in Module Nine.
Outcomes
In this assignment, you will demonstrate your mastery of the following course outcomes:
· QSO.510.1 Provide students with a basic understanding of several quantitative techniques that are used extensively for decision making in business
· QSO.510.2 Enable students to recognize problem areas in their fields of professional responsibilities and to apply the appropriate quantitative methods for obtaining rational solutions
· QSO.510.3 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
· QSO.510.4 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 hypothesis—that 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 data-driven evidence. (QSO.510.3)
a. Topic Selection (QSO.510.1): Select an appropriate topic and provide a detailed explanation of the significance.
b. Citations (QSO.510.1): Paraphrase and/or integrate quotes effectively.
2. Data Collection: Once you finalize your research question, compile your research and collect raw data. (QSO.510.4)
a. Organization (QSO.510.3): Include a clearly stated thesis and a well-organized body section of your paper.
3. Statistical Process (QSO 510.2): Using your knowledge of the scientific method and statistical process to analyze the data:
a. Descriptive Statistics (QSO.510.2): Summarize the population data by describing what was observed in the sample set numerically or graphically.
b. Inferential Statistics (QSO.510.4): 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 (i.e., 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. (QSO.510.4)
c. Null Hypothesis (QSO.510.2): Refer to a general or default position—that 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 (QSO.510.2): 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 task 3-2, 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
Final Submission: Research Paper
In task 9-2, 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 milestone is graded with the Final Product Rubric (below).
Deliverable Milestones
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 |
Proficient |
Needs Improvement |
Not Evident |
Value |
|
Topic Selection QSO 510.1 |
Meets “Proficient” criteria and provides a substantially detailed rationale of topic’s significance (9-10) |
Clearly identifies the topic and provides sufficient rationale of topic’s significance (8) |
Does not clearly identify the topic; rationale is insufficient
(7) |
Does not identify the topic or explain the rationale
(0-6) |
10 |
|
Thesis QSO 510.3 |
Meets “Proficient” criteria, and thesis exhibits strength and insight (9-10) |
Proposes a clear and complete thesis statement
(8) |
Thesis is unclear and/or incomplete
(7) |
Does not propose thesis statement
(0-6) |
10 |
|
Data Collection QSO 510.4 |
Meets “Proficient” criteria and supports explanation with relevant examples from research (9-10) |
Clearly and sufficiently explains statistical process
(8) |
Explanation of statistical process is unclear and/or insufficient
(7) |
Does not explain the statistical process
(0-6) |
10 |
|
Descriptive Statistics QSO 510.2 |
Meets “Proficient” criteria, and explanation is comprehensive
(5) |
Clearly and sufficiently explains how data relates to descriptive statistics
(4) |
Explanation of relationship between data and descriptive statistics is unclear or insufficient (3) |
Does not explain how the data relates to descriptive statistics
(0-2) |
5 |
|
Inferential Statistics QSO 510.4 |
Meets “Proficient” criteria, and explanation is comprehensive
(5) |
Clearly and sufficiently explains how data relates to inferential statistics
(4) |
Explanation of relationship between data and inferential statistics is unclear or insufficient (3) |
Does not explain how the data relates to inferential statistics
(0-2) |
5 |
|
Modeling Relationships Within the Data QSO 510.4 |
“Meets proficient” criteria, and the modeling relationships chosen are appropriate, well justified, and substantially supported (5) |
Clearly illustrates modeling relationships within the data, with sufficient support
(4) |
Modeling relationships are insufficient, inaccurate, and/or unsupported
(3) |
Submission has no documentation of modeling relationships
(0-2) |
10 |
|
Null Hypothesis QSO 510.2 |
Meets “Proficient” criteria, and explanation is insightful and thorough
(9-10) |
Clearly and accurately explains why the null hypothesis is rejected or not rejected
(8) |
Explanation of why null hypothesis is rejected or not rejected is unclear, inaccurate, and/or incomplete (7) |
Does not explain why the null hypothesis is rejected or not rejected
(0-6) |
10 |
|
Statistical Arguments QSO 510.3
|
Meets “Proficient” criteria, and interpretation draws astute conclusions that go beyond existing research (9-10) |
Provides a valid and logical interpretation of statistical thought substantiated by research (8) |
Interpretation of statistical thought is invalid and/or illogical; conclusions are not substantiated by research (7) |
Does not provide an interpretation of statistical thought
(0-6) |
10 |
|
Primary Source Analysis QSO 510.2 |
Meets “Proficient” criteria and includes clear supporting details for the statistical context
(9-10) |
Sufficiently identifies source methodology and clearly relates each to specific statistical context in which it was written (8) |
Analysis of source methodology is insufficient and/or unclear
(7) |
Does not identify source methodology
(0-6) |
10 |
|
Modeling relationships within the data QSO 510.4 |
Meets “Proficient” criteria, and the modeling relationships chosen are appropriate given the data and are well justified and cited (5) |
Submission has noted modeling relationships that match the data, but the source for determining the modeling is not cited (4) |
Submission has noted modeling relationships, but they are not appropriate for the data
(3) |
Submission has no documentation of modeling relationships for the data chosen
(0-2) |
10 |
|
Articulation of Response
|
Submission is free of errors related to citations, grammar, spelling, syntax, and organization and is presented in a professional and easy-to-read format
(9-10) |
Submission has no major errors related to citations, grammar, spelling, syntax, or organization; quotes and paraphrases are effectively integrated
(8) |
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 (7) |
Submission has critical errors related to citations, grammar, spelling, syntax, or organization that prevent understanding of ideas (0-6) |
10 |
|
Earned Total Comments: |
100% |
