Given partial data about an exponential growth trend, fits an ideal exponential growth trend and/or predicts further values.
Sample usage
GROWTH(B2:B10,A2:A10)
GROWTH(B2:B10,A2:A10,A11:A13)
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_yis a two-dimensional array or range, known_data_x must have the same dimensions or be omitted. -
If
known_data_yis 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_yis a single row, each row inknown_data_xis interpreted as a separated independent value, and analogously ifknown_data_yis a single column.
-
-
known_data_x– [ OPTIONAL – {1,2,3,...} with same length as known_data_y by default ] – The values of the independent variable(s) corresponding with known_data_y.- If
known_data_yis 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_yis a single row, each row inknown_data_xis interpreted as a separated independent value, and analogously ifknown_data_yis a single column.
- If
-
new_data_x– [ OPTIONAL – same as known_data_x by default ] – The data points to return the y values for on the ideal curve fit.- The default behavior is to return the ideal curve-fit values for the same
xinputs as the existing data for comparison of known y 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 of y = b*m^x for a curve fit, calculates b if TRUE or forces b to be 1 and only calculates the m values if FALSE.
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.