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:A5,B1:B5)=-0.305309734513
+
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

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}

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


References