Manuals/calci/SLOPE

SLOPE(y,x)

• $y$ is the set of dependent values.
• $x$ is the set of independent values.

Description

• This function gives the slope of the linear regression line through a set of given points.
• The slope of a regression line (b) represents the rate of change in $y$ as ,math> x </math> changes.
• To find a slope we can use the least squares method.
• Slope is found by calculating b as the covariance of x and y, divided by the sum of squares (variance) of x.
• In $SLOPE(y,x),y$ is the array of the numeric dependent values and $x$ is the array of the independent values.
• The arguments can be be either numbers or names, array,constants or references that contain numbers.
• Suppose the array contains text,logical values or empty cells, like that values are not considered.
• The equation for the slope of the regression line is :$b={\frac {\sum (x-{\bar {x}})(y-{\bar {y}})}{\sum (x-{\bar {x}})^{2}}}$. where ${\bar {x}}$ and ${\bar {y}}$ are the sample mean x and y.
• This function will return the result as error when

 1. Any one of the argument is nonnumeric. 
 2. x and y are empty or that have a different number of data points.

Examples

1.y={4,9,2,6,7}

x={1,5,10,3,4}

SLOPE(A1:A5,B1:B5)=-0.305309734513 2.y={2,9,3,8,10,17}

x={4,5,11,7,15,12}

SLOPE(B1:B6,C1:C6)=0.58510638297 3.y={0,9,4}

 x={-1,5,7}

SLOPE(C1:C3)=0.730769230769

See Also

• INTERCEPT
• RSQ
• PEARSON