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.
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.
Use the regression line formula to forecast how much a customer might spend on merchandise if they visited the store 13 times in a 6-month period.
Use the average monthly sales of 2014 ($1,310) as your basis to:
Calculate indices for each month for the next two years.
Graph a time series plot.
In the Data Analysis Toolpak, use Excel’s Exponential Smoothing option in order to:
Apply a damping factor of 0.5 to your monthly sales data.
Create a new time series graph that compares the original and revised monthly sales data.
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