Difference between revisions of "Manuals/calci/SLOPE"

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==Examples==
 
==Examples==
 +
1.
 
{| class="wikitable"
 
{| class="wikitable"
 
|+Spreadsheet
 
|+Spreadsheet
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*=SLOPE(A1:E1,B2:E2)=-0.305309734513
 
*=SLOPE(A1:E1,B2:E2)=-0.305309734513
 +
2.
 
{| class="wikitable"
 
{| class="wikitable"
 
|+Spreadsheet
 
|+Spreadsheet
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| 4 || 5 || 11 || 7 || 15 ||12
 
| 4 || 5 || 11 || 7 || 15 ||12
 
|}
 
|}
2.y={2,9,3,8,10,17}
+
 
x={4,5,11,7,15,12}
 
 
*=SLOPE(A1:F1,A2:F2)=0.58510638297
 
*=SLOPE(A1:F1,A2:F2)=0.58510638297
 +
 
3.y={0,9,4}
 
3.y={0,9,4}
 
   x={-1,5,7}
 
   x={-1,5,7}

Revision as of 06:50, 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

1.

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