GROWTH
Definition
Given partial data about an exponential growth trend, fits an ideal exponential growth trend and/or predicts further values.
Syntax
GROWTH(known_data_y, [known_data_x], [new_data_x], [b])
known_data_y
- The array or range containing dependent (y) values that are already known, used to curve fit an ideal exponential growth curve.If
known_data_y
is a two-dimensional array or range,known_data_x
must have the same dimensions or be omitted.If
known_data_y
is a one-dimensional array or range,known_data_x
may represent multiple independent variables in a two-dimensional array or range. I.e. ifknown_data_y
is a single row, each row inknown_data_x
is interpreted as a separated independent value, and analogously ifknown_data_y
is a single column.
known_data_x
- [ OPTIONAL -{1,2,3,...}
with same length asknown_data_y
by default ] - The values of the independent variable(s) corresponding withknown_data_y
.- If
known_data_y
is a one-dimensional array or range,known_data_x
may represent multiple independent variables in a two-dimensional array or range. I.e. ifknown_data_y
is a single row, each row inknown_data_x
is interpreted as a separated independent value, and analogously ifknown_data_y
is a single column.
- If
new_data_x
- [ OPTIONAL - same asknown_data_x
by default ] - The data points to return they
values for on the ideal curve fit.- The default behavior is to return the ideal curve fit values for the same
x
inputs as the existing data for comparison of knowny
values and their corresponding curve fit estimates.
- The default behavior is to return the ideal curve fit values for the same
b
- [ OPTIONAL -TRUE
by default ] - Given a general exponential form ofy = b*m^x
for a curve fit, calculatesb
ifTRUE
or forcesb
to be1
and only calculates them
values ifFALSE
.
Sample Usage
In order to use the GROWTH formula, start with your edited Excellentable:

Then type in the GROWTH formula in the area you would like to display the outcome:

By adding the values you would like to calculate the GROWTH formula for, Excellentable will generate the outcome:

See Also
TREND
: Given partial data about a linear trend, fits an ideal linear trend using the least squares method and/or predicts further values.
LOGEST
: Given partial data about an exponential growth curve, calculates various parameters about the best fit ideal exponential growth curve.
LINEST
: Given partial data about a linear trend, calculates various parameters about the ideal linear trend using the least-squares method.