# Regressing Nike, Inc. Quarterly Sales

Regressing Nike Inc. Quarterly Sales

pic: Regressing Nike, Inc. Quarterly Sales on price + # of Stores + Amount of advertising spent + # of workers

This needs to be a MULTIPLE LINEAR REGRESSION research paper. Not a multivariate linear regression. We are predicting future situations.

Data requirement:
At least 50 observations or more.
3 explanatory/independent variables.

PAPER FORMAT
Focus on a core analysis like, how does having blank number of stores have on Nike quarterly sales, or some number of amount of advertising spent have on Nike quarterly sales. Each section could/should about 2 or 3 paragraphs.

There needs to be 4 sections.
Section 1: Introduction
Present chosen question like, what is the predicted Nike sales to price, or number of stores, or ads being spent or number of workers.
Why is it relevant? like, this could help other companies.

Section 2: Discussion of the Data
– Source of data.
– Summarize a general sense of the data. Start with summary statistic. Include sample mean and standard deviations.

Section 3: Discussion of Empirical Analysis
– Write empirical model with coefficients. Regression equation.
– Results.
– Provide correct interpretation of results.

Section 4: Conclusion
-If so, how could one apply it to the real world.
-How might your conclusions impact the real world?
-Write about ways that you might take advantage of the data. If you feel your data was not particularly useful explain why?
-Write about what other patterns you may see in the model you created.

One of the following attachments is a sample paper. HOWEVER, rather than being very lengthy and detailed, this paper needs to be more concise. Again, focus on a core analysis, important correlations like, how does having blank number of stores have on Nike quarterly sales, or some number of amount of advertising spent have on Nike quarterly sales. Each section can be about 2 or 3 paragraphs. Not everything needs to be mentioned.

The other attachments is an example of discussing the data and discussing the empirical analysis. Again, as long as key findings are expressed appropriately.

Nike’s sales — https://ycharts.com/companies/NKE/revenues

Total number of Nike retail stores worldwide from 2009 to 2015 — http://www.statista.com/statistics/250287/total-number-of-nike-retail-stores-worldwide/

Nike’s advertising spending in the United States from 2009 to 2014 (in billion U.S. dollars) — http://www.statista.com/statistics/463063/nike-ad-spend-usa/

Number of employees of Nike worldwide from 2009 to 2015 — http://www.statista.com/statistics/243199/number-of-employees-of-nike-worldwide/

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