Difference between revisions of "Manuals/calci/SLOPE"

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==Examples==
 
==Examples==
1.
+
 
{| class="wikitable"
+
1.{| class="wikitable"
 
|+Spreadsheet
 
|+Spreadsheet
 
|-
 
|-
Line 30: Line 30:
 
| 1 || 5 || 10 || 3 || 4
 
| 1 || 5 || 10 || 3 || 4
 
|}
 
|}
 
+
=SLOPE(A1:E1,B2:E2) = -0.305309734513
*=SLOPE(A1:E1,B2:E2)=-0.305309734513
 
 
2.
 
2.
 
{| class="wikitable"
 
{| class="wikitable"

Revision as of 00:03, 22 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

1.{| class="wikitable" |+Spreadsheet |- ! !! A !! B !! C !! D!! E |- ! 1 | 4 || 9 || 2 ||6 || 7 |- ! 2 | 1 || 5 || 10 || 3 || 4 |}

=SLOPE(A1:E1,B2:E2) = -0.305309734513

2.

Spreadsheet
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.y={0,9,4}

 x={-1,5,7}

SLOPE(C1:C3)=0.730769230769

See Also


References