## Linear

Calculates the least squares fit for a line represented by the following equation:

where *m* is the slope and *b* is the intercept.

## Polynomial

Calculates the least squares fit through points by using the following equation:

where *b* and
are constants.

## Logarithmic

Calculates the least squares fit through points by using the following equation:

where *c* and *b* are constants, and ln is the natural logarithm function.

## Exponential

Calculates the least squares fit through points by using the following equation:

where *c* and *b* are constants, and *e* is the base of the natural logarithm.

## Power

Calculates the least squares fit through points by using the following equation:

where *c* and *b* are constants.

## R-squared Value

**Note:** The R-squared value you can display with a trendline is not an adjusted R-squared value. For logarithmic, power, and exponential trendlines, Microsoft Graph uses a transformed regression model.

## Moving Average

**Note:** The number of points in a moving average trendline equals the total number of points in the series less the number you specify for the period.