Part 1—due Sunday July 12
First locate your assigned company revenue data in Company Revenue file under Project folder on D2L and download it to your computer. Copay and paste the data into a new Excel file, or you can copy the data to Minitab directly if comfortable with that. There should be two columns. The first column is the date and the second column is the company revenue. You do not need to use the SG&A data. Your data should start with the oldest date and end with the most recent data. Copy and paste the data to Minitab if needed. Make sure you label your data. Make sure you save the Excel file created or the Minitab spreadsheet. You will need to add more data later.
Below is a fictional example for you to get started. It is expected you to follow the same style: first show graphs/output from Minitab then provide text explanation for all parts of the project. Please use your own wording. Graphs/output without explanation will not be graded.
Revenue analysis for Company Fiction
(You can come up with your own title)
Company Fiction was founded by First name Last name 1923. It is headquartered in City, State, Country. The company is a major electronic retailer. The purpose of this project is to…. Such analysis is important for the company…
Data used in this analysis are quarterly revenue data from Company Fiction between first quarter of 1999 and last quarter of 2016. There are a total of 80 observations. Below is the summary statistics of the data.
The mean revenue is $3762.8 million with a standard deviation of $561.7 million. The highest revenue is $4919 million in the 4th quarter of 2006 while the lowest revenue is $2278 million in the 1st quarter of 1999.
We next examine the time series plot and ACF to determine the stationarity of the data.
Based on the plot, we can tell that the company revenue is not stationary. We can observe both an overall upward trend and seasonality.
The ACF further confirms the seasonality observed in the time series plot. The autocorrelation for the 4th, 8th and 12th lags are significant.
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