Create and calculate the following in Excel®:

1 Conduct a goodness of fit analysis which assesses orders of a specific item by size and items you received by size.

• Conduct a hypothesis test with the objective of determining if there is a difference between what you ordered and what you received at the .05 level of significance.
• Identify the null and alternative hypotheses.

2 Generate a scatter plot, the correlation coefficient, and the linear equation that evaluates whether a relationship exists between the number of times a customer visited the store in the past 6 months and the total amount of money the customer spent.

• Set up a hypothesis test to evaluate the strength of the relationship between the two variables.
• Use a level of significance of .05.

3 Use the regression line formula to forecast how much a customer might spend on merchandise if that customer visited the store 13 times in a 6 month period. Consider the average monthly sales of 2014, $1310, as your base to:

• Calculate indices for each month for the next two years.
• Graph a time series plot.

4 In the Data Analysis Toolpak, use Excel’s Exponential Smoothing option.

• Apply a damping factor of .5, to your monthly sales data.
• Create a new time series graph that compares the original and the revised monthly sales data.

Don’t forget to access the STEP BY STEP instructions for each of the four case study questions embedded in the conversations area for this assignment, click on the small icon in the upper right corner of your screen that looks like a person with a square talk balloon next to its head. Why do it yourself? Let’s do it TOGETHER!

Don’t Go Extinct! Rowr!