The FORECAST.LINEAR function in Excel is a powerful tool for predicting future values based on past data trends. It employs linear regression to draw a forecast, making it essential for data analysis in various fields. This function is especially useful for business, finance, and scientific applications where predicting future outcomes based on historical data is critical.

Syntax

FORECAST.LINEAR(x, known_y's, known_x's)

• x: The data point for which you want to predict a value.
• known_y’s: The dependent array or range of values in the dataset.
• known_x’s: The independent array or range of values that corresponds to the known_y’s.

Example #1

FORECAST.LINEAR(10, B2:B5, A2:A5)

This function predicts the value for x = 10 based on existing values in B2:B5 for y and A2:A5 for x. If B2:B5 contains {3, 4, 5, 6} and A2:A5 contains {1, 2, 3, 4}, the result would be 7.

Example #2

FORECAST.LINEAR(15, C3:C6, B3:B6)

This instance forecasts a future value at x = 15 using values from C3:C6 as known_y’s and B3:B6 as known_x’s. If C3:C6 holds {10, 12, 14, 16} and B3:B6 has {8, 9, 10, 11}, the outcome would be 20.

Example #3

FORECAST.LINEAR(5, D2:D5, C2:C5)

Here, the function estimates a value for x = 5, with D2:D5 as known_y’s and C2:C5 as known_x’s. If D2:D5 equals {1, 3, 5, 7} and C2:C5 corresponds to {1, 2, 3, 4}, the estimated value would be 9.

Error handling

• N/A: This error indicates a missing value in either the known_y’s or known_x’s arrays.
• VALUE!: This occurs when the input values are of different types, such as text instead of numbers.
• REF!: This error arises if the specified ranges are invalid, possibly due to deleted rows or columns.

Conclusion

In summary, the FORECAST.LINEAR function is an invaluable resource for predicting trends based on existing data. By understanding its syntax and potential errors, users can leverage this function to enhance their data analysis, enabling more informed decision-making processes.