In Excel, there are different forecasting functions to predict future results based on existing values. In this article, we will show you how to use the FORECAST function with other forecasting functions in Excel.
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What is FORECAST Function in Excel?
 Description
The FORECAST function is a Statistical function in Excel. It calculates or predicts a future value based on existing value. The existing values are known as xvalues and yvalues and the future value is predicted by using linear regression. For instance, you can predict future numeric values of sales, earnings and expenses, inventory, consumer trends, measurements etc.
 Purpose
To predict or calculate a future value with a linear trend
 Syntax
=FORECAST(x, known_ys, known_xs)
 Arguments Description
Value  Required/Optional  Description 

x  Required  The value for which the future value to predict or calculate 
known_ys  Required  The dependent array or range of data (y values) 
known_xs  Required  The independent array or range of data (x values) 
 Return Value
A predicted or calculated value
Examples of the FORECAST with Other Forecasting Functions in Excel
In this section, you will learn the FORECAST.LINEAR, the FORECAST.ETS, the FORECAST.ETS.CONFINT, the FORECAST.ETS.SEASONALITY and the FORECAST.ETS.STAT function in Excel.
1. FORECAST.LINEAR Function in Excel
FORECAST.LINEAR is formerly known as the FORECAST function in Excel. Microsoft replaced the FORECAST function with the FORECAST.LINEAR in 2016.
 Purpose
This function predicts the future value based on the existing set of values.
 Equation
y = a + bx
Where,
a = constant value, intercept, which follows,
And b = coefficient, the slope of the line, which follows,
Here,
means, the Average value (arithmetic mean) of the sample value.
 Return Value
A calculated future value
Based on the above discussion, the FORECAST.LINEAR formula for our given dataset will be,
=FORECAST.LINEAR(B18,$C$5:$C$16,$B$5:$B$16)
Where,
B18 = The value for which the future value to predict or calculate
$C$5:$C$16 = The dependent array or range of data (y values)
$B$5:$B$16 = The independent array or range of data (x values)
Read More: How to Forecast Sales Using Regression Analysis in Excel (3 Methods)
2. FORECAST.ETS in Excel
The FORECAST.ETS function is used to calculate or predict future value based on existing values by using the AAA version of the Exponential Smoothing (ETS) algorithm.
Here,
AAA = Additive Error, Additive Trend and Additive Seasonality.
ETS = Exponential Triple Smoothing algorithm.
This algorithm loosens up the insignificant deviations in data trends by detecting seasonality patterns and confidence intervals.
 Syntax
=FORECAST.ETS (target_date, values, timeline, [seasonality], [data_completion], [aggregation])
 Argument Description
Value  Required/Optional  Description 

target_date  Required  The timeline for the prediction should be calculated 
values  Required  Existing or historical value(yvalues), dependent array or range of data from which a prediction will be calculated. 
timeline  Required  Numeric independent array or range of values (xvalues) 
[seasonality]  Optional 
Seasonality calculation.

[data_completion]  Optional 
Missing data calculation.

[aggregation]  Optional  Indicates which method to use. Default value is 0 = Average 
 Return Value
A calculation of predicted value
Based on the discussion, the FORECAST.ETS formula for our given dataset shown above will be,
=FORECAST.LINEAR(B18,$C$5:$C$16,$B$5:$B$16)
Where,
B18 = The value for which the future value to predict or calculate
$C$5:$C$16 = The dependent array or range of data (y values)
$B$5:$B$16 = The independent array or range of data (x values)
Read More: How to Forecast Revenue in Excel (6 Simple Methods)
3. FORECAST.ETS.CONFINT
The FORECAST.ETS.CONFINT function returns a confidence interval (CI) for a forecast value at a specified timeline. A confidence level of 90% means the predicted values are expected to fall within this radius from the result that the FORECAST.ETS function produced.
 Syntax
=FORECAST.ETS.CONFINT (target_date, values, timeline, [confidence_level], [seasonality], [data_completion], [aggregation])
 Argument Description
Value  Required/Optional  Description 

target_date  Required  The timeline for the prediction should be calculated 
values  Required  Existing or historical value(yvalues), dependent array or range of data from which a prediction will be calculated. 
timeline  Required  Numeric independent array or range of values (xvalues) 
[confidence_level]  Optional  The confidence level for the calculated confidence interval. A numeric value between 0 and 1 (exclusive). Default 0.95 or 95% 
[seasonality]  Optional  Seasonality calculation.

[data_completion]  Optional  Missing data calculation.

[aggregation]  Optional  Indicates which method to use. Default value is 0 = Average 
 Return Value
Confidence Interval (CI) value
Based on the above discussion, the FORECAST.ETS.CONFINT formula for our given dataset will be,
=FORECAST.ETS.CONFINT(E5,$C$5:$C$16,$B$5:$B$16,G5)
Where,
E5 = The value for which the future value to predict or calculate
$C$5:$C$16 = The dependent array or range of data (y values)
$B$5:$B$16 = The independent array or range of data (x values)
G5 = Confidence level
Read More: Time Series Forecasting Methods in Excel
4. FORECAST.ETS.SEASONALITY
The FORECAST.ETS.SEASONALITY function is used to return the length of a repetitive pattern in a specified timeline.
 Syntax
=FORECAST.ETS.SEASONALITY (values, timeline, [data_completion], [aggregation])
 Argument Description
Value  Required/Optional  Description 

values  Required  Existing or historical value(yvalues), dependent array or range of data from which a prediction will be calculated. 
timeline  Required  Numeric independent array or range of values (xvalues) 
[data_completion]  Optional  Missing data calculation.

[aggregation]  Optional  Indicates which method to use. Default value is 0 = Average 
 Return Value
Season length in a specified timeline
Based on the above discussion, the FORECAST.ETS.SEASONALITY formula for our given dataset shown above will be,
=FORECAST.ETS.SEASONALITY($C$5:$C$16,$B$5:$B$16)
Where,
$C$5:$C$16 = The dependent array or range of data (Score column as y values)
$B$5:$B$16 = The independent array or range of data (ID column as x values)
Read More: How to Forecast Growth Rate in Excel (2 Methods)
5. FORECAST.ETS.STAT in Excel
The FORECAST.ETS.STAT function returns a statistical value relating to the time series forecasting with the FORECAST.ETS function.
Syntax
=FORECAST.ETS.STAT (values, timeline, statistic_type, [seasonality], [data_completion], [aggregation])
 Argument Description
Value  Required/Optional  Description 

values  Required  Existing or historical value(yvalues), dependent array or range of data from which a prediction will be calculated. 
timeline  Required  Numeric independent array or range of values (xvalues) 
statistic_type  Required  The type of statistical value to return. The table below shows the 8 possible types and their description,

[seasonality]  Optional  Seasonality calculation.

[data_completion]  Optional  Missing data calculation.

[aggregation]  Optional  Indicates which method to use. Default value is 0 = Average 
 Return Value
A statistical result
The formula for the FORECAST.ETS.STAT function with different statistic types is shown in the picture below,
The formula,
=FORECAST.ETS.SEASONALITY($C$5:$C$16,$B$5:$B$16,1)
Where,
$C$5:$C$16 = The dependent array or range of data (Score column as y values)
$B$5:$B$16 = The independent array or range of data (ID column as x values)
1 = Alpha statistic type (this numeric argument can be anything from 1 to 8 based on the requirement)
Read More: How to Forecast Sales Growth Rate in Excel (6 Methods)
Conclusion
This article explained in detail how to use the FORECAST and other forecasting function in Excel with examples. I hope this article has been very beneficial to you. Feel free to ask if you have any questions regarding the topic.