{"id":198,"date":"2025-07-15T13:34:46","date_gmt":"2025-07-15T13:34:46","guid":{"rendered":"https:\/\/functiontranslator.com\/2021\/02\/12\/forecast-ets-stat\/"},"modified":"2021-02-13T11:34:08","modified_gmt":"2021-02-13T11:34:08","slug":"forecast-ets-stat","status":"publish","type":"post","link":"https:\/\/functiontranslator.com\/en\/forecast-ets-stat\/","title":{"rendered":"FORECAST.ETS.STAT"},"content":{"rendered":"

The following description offers a comprehensive guide on how to use the FORECAST.ETS.STAT function in Microsoft Excel and Google Sheets, including practical examples of its applications and methods for deploying this function effectively.<\/p>\n

Overview of the Function<\/h2>\n

The FORECAST.ETS.STAT function provides statistical information about an exponential smoothing forecast. Available in both Microsoft Excel and Google Sheets, this function proves extremely useful for analyzing time-dependent data.<\/p>\n

Example Scenario<\/h2>\n

Imagine you possess historical monthly sales data for a product. You intend to employ exponential smoothing to predict sales for the upcoming month and need to examine the statistical details of this forecast.<\/p>\n

Syntax<\/h2>\n

The syntax for using the FORECAST.ETS.STAT function is as follows:<\/p>\n

FORECAST.ETS.STAT(target_date, data_range, timeline, [seasonality], [data_completion], [aggregation])<\/code><\/pre>\n\n\n\n\n\n\n\n\n
Parameter<\/th>\nDescription<\/th>\n<\/tr>\n
target_date<\/td>\nThe specific date for which the forecast is desired.<\/td>\n<\/tr>\n
data_range<\/td>\nThe range containing historical data points.<\/td>\n<\/tr>\n
timeline<\/td>\nA series of values delineating the timeline for the data points.<\/td>\n<\/tr>\n
seasonality<\/td>\n(Optional) Defines the cycle length of the seasonal pattern within the data.<\/td>\n<\/tr>\n
data_completion<\/td>\n(Optional) Indicates the approach for dealing with missing data points.<\/td>\n<\/tr>\n
aggregation<\/td>\n(Optional) Determines the method to handle duplicates within the data points.<\/td>\n<\/tr>\n<\/table>\n
Example<\/h2>\n
Consider the example dataset below:<\/p>\n\n\n\n\n\n
Date<\/th>\nSales<\/th>\n<\/tr>\n
Jan<\/td>\n100<\/td>\n<\/tr>\n
Feb<\/td>\n110<\/td>\n<\/tr>\n
Mar<\/td>\n120<\/td>\n<\/tr>\n<\/table>\n
We can apply the FORECAST.ETS.STAT function to predict April’s sales and extract statistical information with the following formula:<\/p>\n
=FORECAST.ETS.STAT(\"Apr\", B2:B4, A2:A4)<\/code><\/pre>\n
This computation will deliver statistical insights for the April forecast, based on the historical sales data from January through March.<\/p>\n
By familiarizing yourself with the syntax and practical application illustrated above, you can proficiently utilize the FORECAST.ETS.STAT function in Excel and Google Sheets to analyze and predict outcomes for time series data using exponential smoothing.<\/p>\n","protected":false},"excerpt":{"rendered":"
Returns a statistical value as a result of time series forecasting<\/p>\n","protected":false},"author":1,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[203],"tags":[],"class_list":["post-198","post","type-post","status-publish","format-standard","hentry","category-statistical"],"acf":[],"yoast_head":"\nExcel FORECAST.ETS.STAT Function \u2013 How It Works, Formula Examples and Syntax<\/title>\n<meta name=\"description\" content=\"Learn what the Excel FORECAST.ETS.STAT function does. 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