Report the known project with all information given in problem.

This course project will determine 50 percent of your final grade and hence, needs to reflect the same in the quality of your data interpretation of the results, ability to communicate the results to a layman with a non statistics background and presentation of the report. In this project, you, the students will act as consultants hired to complete a quantitative project by me, your client. Your job will be to take the dataset, analyze it using the tools and techniques taught in this course and come up with a high quality report that will demonstrate both your understanding of the curriculum of this course and your presentation skills.

The final report must be fully typed, including all the relevant methodology, equations, plots, etc. The final document must be no longer than 12 pages long, including a cover sheet and a page for references. So, you will have 10 full pages in the middle to make your case. The references page at the end should include pointers to things you've utilized in the report, including pages of the textbook with the relevant theory, websites you visited, articles you might've read, etc.

Any handwritten material and/or material going over the page limit of 10 will be discarded. Brevity is a crucial component of clarity.

•Presentation - This would cover the looks and aesthetics of the report. Things such as the structure and flow of the report, placement and labelling of graphs/plots/tables, conciseness and clarity of the writing will matter.

•Data Analysis & Numbers - This will cover your use of JMP, any manual calculations you may perform, dealing with outliers, equations, etc.

•Interpretation of Results - This will cover interpreting results in plain English for audiences that do not have a statistics background, justification provided for dealing with outliers, transformations, etc.
The following is a suggestion for how a report might be organized. This is by no means stringent. Feel free to add/remove sections from this list.

•Introduction: This section should be a precise description of your aims for this project. What are you investigating and what do potentially hope to find or prove? Did you need to collect additional data other than the data set provided? If so, how did you go about collecting it? Why and how would you be potentially useful in real life? Conclude this section with your plan of action and a couple of lines on the structure of your report.

•Data Description: What is the population from which your sample has been taken? Description of data taken from other sources. Preliminary analysis using histograms, box plots, scatter plots, etc. and investigation of outliers. Do you keep or discard identified outliers? Give good reason for either way.

•Analysis & Results: This section is the body of your report. Use it to present your use of the tools and techniques taught in this course. Justify the use of any hypothesis tests, regressions, data transformations, etc. This is essentially a description of how you did the analysis and the numbers/equations you get. All graphs, plots and tables should have appropriate captions. Remember, figures support your text, not the other way round.

•Conclusions: A brief summary of your most important findings. Discuss any shortcomings in your study and potential improvements. You can also use this section to suggest improvements to your project, and how you would go about doing the project if you had more time and resources available.

•References: This must be the last page of the report, not counted in the maximum often methodology, equations, plots n pages you have for the rest.You're Project Topic

We are interested in investigating the prices of books on online vendors such as Amazon, Barnes and Nobles, Borders, etc. The plan here is to detect whether there are significant price differences in books across these vendors. Pick out lists of bestsellers books from an independent source such the New York Times or Time Magazine. By independent, we mean that the bestsellers list should not be generated by any of the bookstores being looked at. You can get creative here and refine your list of books by genre, hardback/paperback, etc. in addition, can you think of any predictor variables for book prices and do regression analysis?