# Question

Reconsider Prob. 27.7-11. Despite some fluctuations from year to year, note that there has been a basic trend upward in the annual demand for copper ore over the past 10 years. Therefore, by projecting this trend forward, causal forecasting can be used to forecast demands in future years by letting the year be the independent variable and the demand be the dependent variable.

(a) Plot the data for the past 10 years (Years 1 through 10) on a two-dimensional graph with the year on the horizontal axis and the demand on the vertical axis.

T (b) Find the formula for the linear regression line that fits these data.

(c) Plot this line on the graph constructed in part (a).

(d) Use this line to forecast demand next year (Year 11).

(e) Use this line to forecast demand in Year 15.

(f) What does the formula for the linear regression line indicate is roughly the average growth in demand per year?

(g) Use the linear regression procedure in the forecasting area of your IOR Tutorial to generate a graph of the data and the linear regression line. Then experiment with the data to see how the linear regression line shifts as you drag any of the data points up or down.

(a) Plot the data for the past 10 years (Years 1 through 10) on a two-dimensional graph with the year on the horizontal axis and the demand on the vertical axis.

T (b) Find the formula for the linear regression line that fits these data.

(c) Plot this line on the graph constructed in part (a).

(d) Use this line to forecast demand next year (Year 11).

(e) Use this line to forecast demand in Year 15.

(f) What does the formula for the linear regression line indicate is roughly the average growth in demand per year?

(g) Use the linear regression procedure in the forecasting area of your IOR Tutorial to generate a graph of the data and the linear regression line. Then experiment with the data to see how the linear regression line shifts as you drag any of the data points up or down.

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