Linear Trend Lines. Y t = b 0 + b 1 X t Where Y t is the dependent variable being forecasted X t is the independent variable being used to explain Y. In Linear Trend Lines, X t is assumed to be t. b 1 is the slope of the line, determined by Excel
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By Changing seasonal indices, b0 and b1
Subject to average seasonal index = 100%
and seasonal indices>=0
=1.44* 199.63 = 288.4
You want to examine the linear dependency of the annual sales of produce stores on their size in square footage. Sample data for seven stores were obtained. Find the equation of the straight line that fits the data best.
Annual Store Square Sales Feet ($1000)
1 1,726 3,681
2 1,542 3,395
3 2,816 6,653
4 5,555 9,543
5 1,292 3,318
6 2,208 5,563
7 1,313 3,760
From Excel Printout:
Yi = 1636.415 +1.487Xi
The slope of 1.487 means that for each increase of one unit in X, we predict the average of Y to increase by an estimated 1.487 units.
The model estimates that for each increase of one square foot in the size of the store, the expected annual sales are predicted to increase by $1487.