Free Ebook cover Complete Excel Course for Beginners

Complete Excel Course for Beginners

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Time series forecasting

Capítulo 31

Estimated reading time: 2 minutes

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Time series forecasting is a technique widely used in several areas, such as finance, economics, marketing, among others. It consists of using historical data to predict future values ​​of a given variable.

In Excel, there are several tools that can be used to perform time series forecasts. One of the most used is the FORECAST.LINEAR function, which uses the linear regression method to predict future values.

To use this function, you need to have a historical series of data. For example, if we want to predict the number of sales of a certain product in the coming months, we need to have sales data for the last few months.

Once you have the historical data, you must select the cell where the forecast will be displayed and use the FORECAST.LINEAR function, informing the historical data and the number of periods you want to forecast. For example:

=LINEAR FORECAST(B2:B13,A2:A13,A14:A16)

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In this example, the historical data is in column A, from A2 to A13, and the corresponding values ​​are in column B, from B2 to B13. Cell A14 contains the value for the next period, and cells A15 and A16 contain the values ​​for the next two periods.

In addition to the FORECAST.LINEAR function, Excel also has other tools for forecasting time series, such as Data Analysis and Solver. These tools are more advanced and can be used to predict more complex values.

In summary, time series forecasting is an important technique for many areas, and Excel offers several tools to perform these forecasts. It's important to remember that forecast results are estimates only and may vary based on a variety of external factors.

Now answer the exercise about the content:

_What is the most used Excel function for forecasting time series?

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The most used Excel function for forecasting time series is the FORECAST.LINEAR function, as it is specifically designed to predict future values based on historical data, making it an ideal choice for time series analysis.

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Hypothesis analysis

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