# Question

These data contain quarterly net income (in millions of dollars) of Wal-Mart from 1990 through the end of 2011 (88 quarters). Net income is the difference between sales and the cost of running the business including both the merchandise and the labor to make the sale.

(a) Create a scatterplot for net income on date. Is the pattern linear?

(b) Fit a linear trend to the net income. Interpret the slope and intercept.

(c) Plot the residuals from this linear trend on date. Do the residuals show random variation, or do you see patterns in the mean or variation of the residuals?

(d) Create a scatterplot for net income on date, but use a log scale for the y-axis. Compare this view of the data to the initial plot of net income versus date.

(e) Fit the equation loge (Net Income) = b0 + b1 Date. Interpret the slope in the ft of this equation.

(f) What pattern remains in the residuals from the ft of the log of net income on date? Can you explain what’s happening?

(g) Which equation offers the better summary of the trend in net income

(a) Create a scatterplot for net income on date. Is the pattern linear?

(b) Fit a linear trend to the net income. Interpret the slope and intercept.

(c) Plot the residuals from this linear trend on date. Do the residuals show random variation, or do you see patterns in the mean or variation of the residuals?

(d) Create a scatterplot for net income on date, but use a log scale for the y-axis. Compare this view of the data to the initial plot of net income versus date.

(e) Fit the equation loge (Net Income) = b0 + b1 Date. Interpret the slope in the ft of this equation.

(f) What pattern remains in the residuals from the ft of the log of net income on date? Can you explain what’s happening?

(g) Which equation offers the better summary of the trend in net income

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