Calculate the slope of a linear regression line.

`SLOPE(known_y's, known_x's)`

- known_ys - required array of numeric data points (dependent values)
- known_xs - required array or range of data points that are known

`=SLOPE(B5:B9,C5:C9)`

The SLOPE function is a powerful Sourcetable function that calculates the slope of a regression line from a given set of values. For example, this calculates the slope of the regression line between the two sets of values in columns B and C, from rows 5 to 9.

`=SLOPE(B5:B9,C5:C9)`

In this example, let's say that the values in column B are a set of exam scores, and the values in column C are a set of corresponding letter grades. The SLOPE function can be used to calculate the average grade change for each exam point increase. For example, this returns a value of -2, which means that for each one point increase in the exam score, the average grade is decreased by 2.

`=SLOPE(A1:A5,B1:B5)`

The SLOPE function can also be used to calculate the slope of a linear regression line between two different data sets. For example, this can be used to calculate the slope of the regression line between the two sets of data in columns A and B, from rows 1 to 5. The result of this calculation is the slope of the regression line between the two sets of data.

`=SLOPE(A1:A5,B1:B5)`

The SLOPE function can also be used to calculate the correlation coefficient of a given set of data. For example, the formula can be used to calculate the correlation coefficient of the two sets of data in columns A and B, from rows 1 to 5. The result of this calculation is the correlation coefficient of the two sets of data.

The SLOPE function is used to calculate the slope of a linear regression line by taking the vertical and horizontal distances between two points on the line. It ignores text, logical values, and empty cells, and returns an error if the known_y's and known_x's are empty or have a different number of data points.

- The SLOPE function calculates the slope of a regression line through two different arrays or ranges of data points, known as the known_ys and known_xs arguments.
- The known_ys argument is an array or range of data points that are known, while known_xs is an array of numeric data points or a range of data points.
- The result of the SLOPE function is a calculated slope as a number.

The first argument of the SLOPE function is known_y's. This argument is required and it is an array or cell of numeric dependent data points.

The second argument of the SLOPE function is known_x's. This argument is also required and it is the set of independent data points.

The SLOPE function is a statistical function used to calculate the slope of a line based on two data sets. It is useful for analyzing trends in a set of data.

The arguments of the SLOPE function are known_y's and known_x's. Both arguments are required, with known_y's being an array or cell of numeric dependent data points and known_x's being the set of independent data points.