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Overview
For this group project you'll be responsible to write a multivariate analysis of a dataset of your choice using Excel. Specifically, you'll be responsible for:
1. Gathering data on a particular topic of your choice (meeting requirements below)
2. Analyzing and understanding the data using Excel.
3. Estimating the effect of a main independent variable on a dependent variable using multiple regression.
4. Write a 6-8 page report (including graphs and tables).
5. Deliver a 5-7 minute presentation followed by a 5 minute Q&A
Deliverables
I expect two documents per group:
1. A .pdf document written report, this should include all the relevant graphs and figures.
2. An .xlsx document with the original dataset, data dictionary (explain what the variables are if not obvious from the variable name) and any calculation/analysis produced for the project. There should also be a link with a source from the data.
Gathering Data
As long as you follow these restrictions you are free to use any data source of your choice:
• At least 8 variables
• Must include at least two categorical and two numerical variables
• More than 200 observations (but not too big – less than 100,000)
• No simulated data or data from experiments
• No cleaned data from statistics/economics textbooks
I encourage you to try to find data on things that you are curious or passionate about: if you like travel maybe gather some data on tourist destinations; there are almost unlimited statistics from sports; use this project as an opportunity to do some research on academic programs you may want to pursue in the future or do some job market research; etc.
Structure of the paper
Introduction (This should be BRIEF)
What is the motivation for your analysis? Explain the problem and why it is important. Brief description of your data and the problem you will try to answer using regression. This should be entertaining, engaging, interesting! Make the readers want to keep going!
Data Description
Provide description of data using summary statistics, correlation tables, visualizations as needed. Explain any important/relevant details of your data that they reader should know. Introduce the potential relationship between your Y and X variables of interest.
Regression Models/Results
Estimate a single variable regression using your dependent and main independent variable. Then add the other important X variables and arrive at your final model. Present any models you run in a single table as shown in class. Discuss the results, but not just simply interpret every single value. Explain to the reader where their focus should be. Do you care most about accurately understanding the relationship between a particular X variable and Y, or do you want the most accurate model possible to try and forecast Y? Follow through on your goal.
Conclusion
Re-state the main results of your analysis and explains how the analysis helps answer your question of interested. This is the part where you explain the “So what?” question to your reader as to why this analysis helped answer or question and what decisions can be made as a result. Close the paper in a meaningful way for the reader.
Additional Guidelines and Recommendations
• All your graphs should have a title, axis labels and legend when necessary. Include the units in which variables are measured if its not immediately clear. The graphs and tables can be embedded within the paper (not just all at the end).
• Make sure that the numbers in your graphs and tables are legible.
• Label your worksheets with descriptive titles.
• Explore other forms of data visualization besides scatterplots. Don't be afraid of grouping a numerical variable.
• Use a consistent style. If you are using Times New Roman when writing your document, make sure you are using the same font when generating your graphs and tables in excel. The same goes for combination of font colors and sizes.
• Save your graphs from Excel as .png or .jpg and then add them to your document. Additionally, you can copy-paste from Excel into MS Word or Pages. Do not use print-screen/cropping tool.
• Enumerate your figures for better citation. It is better to say "In Figure A we found..." than "In the histogram on page 3 we found...".
• Don't be prescriptive or argumentative until the conclusion. A descriptive analysis must be as objective of a representation of the data as possible. Refrain yourself from giving policy recommendations or your personal opinions until you have the opportunity to give the “SO WHAT?” part of the conclusion.
• Always follow these three principles when writing about data: brevity, clarity, and honesty.
• Include a cover page with the following information: name of each student and BU ID, course ID, name of the instructor, date and an engaging title to let the reader know what they are about to get into. This page does not count towards the page limit.