Describe and interpret the general measurements of your data

1. Introduction
a. Whats so interesting about your topic? Why did you choose it?
b. Lead us into your paper.
c. Describe your general hypothesis or hypotheses for your paper.
2. Literature Review
a. What have other people done with your topic? What were their conclusions?
b. If not specifically, then more broadly.
c. This should be mostly academic sources.
3. Methodology
a. Generally describe the method you are going to use.
i. OLS
ii. T-test
iii. Correlation matrix
b. Identify and define your variables as they will be used in your model.
c. Specify your hypothesized model.
d. Predict the signs that will accompany your slope coefficients based on theory and
knowledge.
4. Descriptive Statistics
a. Identify the source of your data
b. Describe and interpret the general measurements of your data
i. Sample size
ii. Mean, median, SD, etc.
iii. Correlation matrix, critical value, interpretations.
iv. You decide which of the descriptive statistics are most important, do not
simply list everything you can possibly calculate.
5. Inferential Statistics
a. T-test
b. Anova
c. Linear Regression*
i. *Linear regression is the only required component in the Inferential
Statistics section.
ii. Provide residual analysis and discuss the outcomes
1. Was there heteroskedasticity? How about multicollinearity?
2. Did you transform any variables? Why?
d. Describe the process you used and offer insight into why you proceeded as you did.
6. Results/Analysis
a. Analyze and interpret your results.
i. Interpret your T-test or Anova results, if necessary.
ii. Interpret the slope coefficients of your best model.
1. Did the signs align with theory and knowledge?
iii. Interpret your R^2 or adjusted R^2 value

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