Fits polynomial curves using regression.

`TREND(known_y's, known_x's, new_x's, [const], [stats])`

- arg_1 - required
- arg_2 - [OPTIONAL]

The TREND function is a statistical function in Sourcetable that can be used to predict future values from existing values. It takes three arguments: known_y's, known_x's, and new_x's. The known_y's argument is an array or range of dependent values that you already know. The known_x's argument is an array or range of independent values that are associated with the known_y's values. The new_x's argument is an array or range of independent values that you want to use to predict new_y's values.

For example, say you have a list of ten stock prices, and you want to predict what the stock price will be in 15 days. You can use the TREND function to do this. The known_y's argument would be a range of the ten stock prices, and the known_x's argument would be the number of days between each stock price. The new_x's argument would be the number of days for which you want to predict the stock price. The function will return the predicted stock price.

The TREND function can be used to extrapolate data, meaning to use the existing data to predict values outside the range of the existing data. For example, if you have a range of temperatures for a certain day, you could use the TREND function to predict what the temperature will be the next day. The known_y's argument would be a range of the temperatures, and the known_x's argument would be the days. The new_x's argument would be the day for which you want to predict the temperatures.

The TREND function is used to calculate a linear trend line through a given set of data points and to extend the line forward or backward in time. It is useful for predicting future values or estimating values for a specific time period.

- TREND is a Sourcetable function that is used to calculate a linear trend line for a set of data points.
- The function takes three arguments: x values, y values and new x values. The function returns the y values that correspond to the new x values.
- The function can be used to forecast future values.
- TREND automatically calculates the linear regression coefficients, which can then be used to calculate the slope and intercept of the trend line.
- The TREND function can also be used to calculate the correlation coefficient (r-squared) between the x and y values.

The TREND function is a statistical function in Sourcetable used to calculate linear predictions from existing data. It is often used to forecast future values based on historical data.

The TREND function takes existing data and uses it to calculate a linear trend line that best fits the data points. It then uses the trend line to extrapolate future values.

To use the TREND function, you need to have a set of existing data that you want to use to calculate the trend line. You will then enter the TREND function in a cell, specifying the data points you want to use. The function will return the calculated trend line.

The syntax for the TREND function is: TREND(known_y's,known_x's,new_x's,const).

- known_y's - The range of dependent values (y-values) that are already known.
- known_x's - The range of independent values (x-values) that are already known.
- new_x's - The range of x-values for which you want to predict the corresponding y-values.
- const - A logical value specifying whether to force the constant b0 to equal 0. If omitted, it will default to TRUE.

The TREND function is used to calculate a linear trend line for a set of existing data points. The LINEST function is used to calculate the coefficients of a linear regression equation. The TREND function uses the coefficients from the LINEST function to extrapolate future values.