Excel

FORECAST.LINEAR: Excel Formulae Explained

How do you use FORECAST.LINEAR in Excel?

The FORECAST.LINEAR function in Excel is used to predict future values in a linear trendline. The function takes in three input arguments: the first is the array of data points, the second is the array of coefficients, and the third is the intercept. The function then returns the predicted value for the next data point in the array.

What is the syntax of FORECAST.LINEAR in Excel?

The syntax of FORECAST.LINEAR in Excel is as follows: =FORECAST.LINEAR(y_range,x_range,confidence_level) The function takes in three inputs: y_range is the range of cells that contain the historical data points, x_range is the range of cells that contain the corresponding x-values, and confidence_level is the desired level of confidence. The function then outputs a predicted y-value for each x-value in the x_range.

What is an example of how to use FORECAST.LINEAR in Excel?

The FORECAST.LINEAR function is used to predict future values in a linear trend. The function takes four arguments: the independent variable (x), the dependent variable (y), the starting point of the trend, and the number of periods over which the trend will be extrapolated. The function will return the predicted y-value for a given x-value.

For example, if you wanted to predict the future sales of a product based on historical sales data, you could use the FORECAST.LINEAR function. The independent variable would be the historical sales data, the dependent variable would be the future sales, the starting point of the trend would be the current sales, and the number of periods over which the trend will be extrapolated would be the number of future months. The function would then return the predicted future sales for each month.

When should you not use FORECAST.LINEAR in Excel?

FORECAST.LINEAR should not be used when there is evidence of nonlinearity in the data or when the analyst wishes to model the relationship between two or more independent variables and the dependent variable. Nonlinearity can be detected through graphical examination of the data or through the use of statistical tests. If the analyst suspects a nonlinear relationship, then a nonlinear function should be used. FORECAST.LINEAR should also not be used when the analyst wishes to model the relationship between two or more independent variables and the dependent variable is time-series data. In this case, a time-series regression model should be used.

What are some similar formulae to FORECAST.LINEAR in Excel?

The Excel FORECAST.LINEAR function is used to predict future values in a linear trend. The function takes four arguments: the input series, the number of periods for the prediction, the lower bound, and the upper bound. The input series is the data set that you want to predict future values for. The number of periods is the number of periods over which you want to make the prediction. The lower bound and upper bound are the bounds for the prediction. The function will return the predicted value for the input series at the given number of periods.

There are several other functions in Excel that can be used to predict future values. The FORECAST.POINT function predicts a single future value based on a linear trend. The function takes three arguments: the input series, the number of periods for the prediction, and the point in time for the prediction. The input series is the data set that you want to predict future values for. The number of periods is the number of periods over which you want to make the prediction. The point in time is the point in time at which you want to make the prediction. The function will return the predicted value for the input series at the given point in time.

The TREND function can be used to predict future values in a linear trend. The function takes four arguments: the input series, the number of periods for the prediction, the lower bound, and the upper bound. The input series is the data set that you want to predict future values for. The number of periods is the number of periods over which you want to make the prediction. The lower bound and upper bound are the bounds for the prediction. The function will return the predicted values for the input series at the given number of periods.

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