Difference between revisions of "Manuals/calci/SLOPE"
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− | <div style="font-size:30px">'''SLOPE( | + | <div style="font-size:30px">'''SLOPE (KnownYArray,KnownXArray)'''</div><br/> |
− | *<math> | + | *<math> KnownYArray </math> is the set of dependent values. |
− | *<math> | + | *<math> KnownXArray </math> is the set of independent values. |
+ | **SLOPE(), returns the slope of the linear regression line. | ||
==Description== | ==Description== | ||
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*To find a slope we can use the least squares method. | *To find a slope we can use the least squares method. | ||
*Slope is found by calculating b as the co-variance of <math>x</math> and <math>y</math>, divided by the sum of squares (variance) of <math>x</math>. | *Slope is found by calculating b as the co-variance of <math>x</math> and <math>y</math>, divided by the sum of squares (variance) of <math>x</math>. | ||
− | *In <math>SLOPE( | + | *In <math>SLOPE (KnownYArray,KnownXArray)</math>, <math>KnownYArray </math> is the array of the numeric dependent values and <math> KnownXArray </math> is the array of the independent values. |
*The arguments can be be either numbers or names, array, constants or references that contain numbers. | *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. | *Suppose the array contains text, logical values or empty cells, like that values are not considered. | ||
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*This function will return the result as error when | *This function will return the result as error when | ||
1. Any one of the argument is non-numeric. | 1. Any one of the argument is non-numeric. | ||
− | 2. <math> | + | 2. <math>KnownYArray</math> and <math>KnownXArray</math> are empty or that have a different number of data points. |
==Examples== | ==Examples== |
Latest revision as of 16:12, 1 August 2018
SLOPE (KnownYArray,KnownXArray)
- is the set of dependent values.
- is the set of independent values.
- SLOPE(), returns the slope of the linear regression line.
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 co-variance of and , divided by the sum of squares (variance) of .
- 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 non-numeric. 2. and are empty or that have a different number of data points.
Examples
1.
A | B | C | D | E | |
---|---|---|---|---|---|
1 | 4 | 9 | 2 | 6 | 7 |
2 | 1 | 5 | 10 | 3 | 4 |
=SLOPE(A1:E1,A2:E2) = -0.305309734513
2.
A | B | C | D | E | F | |
---|---|---|---|---|---|---|
1 | 2 | 9 | 3 | 8 | 10 | 17 |
2 | 4 | 5 | 11 | 7 | 15 | 12 |
=SLOPE(A1:F1,A2:F2) = 0.58510638297
3.
A | B | C | |
---|---|---|---|
1 | 0 | 9 | 4 |
2 | -1 | 5 | 7 |
=SLOPE(C1:C3) = 0.730769230769
Related Videos
See Also
References