Preparation Instructions: You will work individually on this data project. At the end of the semester, you will turn in a data project paper and prepare an analysis presentation. To begin your research, here are some useful resources to get you started: • United States Census Bureau • CIA World Fact Book • U.S. Department of Commerce Note: You are not limited to using these resources since you are encouraged to use data researched from library resources, work data, etc. A sample PowerPoint (PPT) Presentation is available on the Start Here page. Please review and contact your professor with any questions. Research Paper 1) Prepare your paper in Microsoft Word. 2) Use Times New Roman, 12-point font in black, single-spaced, 1-inchmargins. 3) Your paper should be about eight to ten pages in length. 4) The paper should include the following nine components (print this sheet down and cross off each element as you add it into your research report) : a) Tables, b) Charts, c) Appendix with graphs, d) An Executive Summary, e) An Introduction, f) A Description of the Nature of the Data, g) An Overview of the Data Collection Methodology, h) An Explanation of How in your processes the data is used, and i) The Analysis Results
Research Paper 1. You will work diligently to secure a data set. The data set can be from your employer (with appropriate authorization), libraries, data warehouses (with consent from the owner), public sources like the U.S. Census Bureau or the CIA,etc. 2. The requirement is that you will need to have at least 20 parameters and over 5,000 records. 3. You are to analyze the data and glean from the data some meaningful, insightful, and significant results and trends that help your respective research area’s decisionmaking process. You are free to use any of the analytical tools covered in class, and beyond that, you learned independently. 4. As a minimum, you must use all the following analyses, including descriptive statistics, measures of central tendency and variations, correlation, confidence intervals, hypothesis testing, chi-square test, ANOVA, and linearregression.
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