Difference between revisions of "Manuals/calci/SLOPE"
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==Examples== | ==Examples== | ||
+ | {| class="wikitable" | ||
+ | |+Spreadsheet | ||
+ | |- | ||
+ | ! !! A !! B !! C !! D!! E | ||
+ | |- | ||
+ | ! 1 | ||
+ | | 4 || 9 || 2 ||6 || 7 | ||
+ | |- | ||
+ | ! 2 | ||
+ | | 1 || 5 || 10 || 3 || 4 | ||
+ | |} | ||
+ | |||
1.y={4,9,2,6,7} | 1.y={4,9,2,6,7} | ||
x={1,5,10,3,4} | x={1,5,10,3,4} | ||
− | SLOPE(A1: | + | SLOPE(A1:E1,B2:E2)=-0.305309734513 |
2.y={2,9,3,8,10,17} | 2.y={2,9,3,8,10,17} | ||
x={4,5,11,7,15,12} | x={4,5,11,7,15,12} | ||
Line 27: | Line 39: | ||
x={-1,5,7} | x={-1,5,7} | ||
SLOPE(C1:C3)=0.730769230769 | SLOPE(C1:C3)=0.730769230769 | ||
− | |||
==See Also== | ==See Also== |
Revision as of 06:46, 21 January 2014
SLOPE(y,x)
- is the set of dependent values.
- 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 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 is the array of the numeric dependent values and 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 :. where and 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
A | B | C | D | E | |
---|---|---|---|---|---|
1 | 4 | 9 | 2 | 6 | 7 |
2 | 1 | 5 | 10 | 3 | 4 |
1.y={4,9,2,6,7}
x={1,5,10,3,4}
SLOPE(A1:E1,B2:E2)=-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