Regression Trend Lines
Some of the forecast types you can choose are presented below.
All of these forecasts are fit to your data using regression
analysis.
Linear
Linear forecast with confidence limits
n is a usersupplied constant between 0 and 100
defining the confidence interval. For example, a value of 90 will
cause confidence lines to be drawn such that the value being
forecast is 90% likely to be between the lines (5% chance of
being above the upper line and 5% below the lower). To display
lines at one standard deviation from the prediction line, use
n = 68.3. To display lines at two standard deviations,
use n = 95.5%.
In order for the confidence limits to properly reflect
uncertainty in the forecast, the underlying data must conform to
assumptions inherent in the linear regression model.
Specifically, y must be a linear function of x;
and, the residuals must be normally distributed.
Hyperbolic
Logarithmic
Square Root
Quadratic
Polynomial
n is a usersupplied constant.
Power
Exponential
Seasonal trend
p1 and p2 are usersupplied season and cycle
periods. All other constants are calculated automatically.
