Difference between revisions of "Manuals/calci/INTERCEPT"

From ZCubes Wiki
Jump to navigation Jump to search
 
(15 intermediate revisions by 4 users not shown)
Line 1: Line 1:
<div style="font-size:30px">'''INTERCEPT(y,x)'''</div><br/>
+
<div style="font-size:30px">'''INTERCEPT (KnownYArray,KnownXArray)'''</div><br/>
*<math>y</math> is the set of dependent data  
+
*<math>KnownYArray</math> is the set of dependent data  
* <math>x</math> is the set of independent data.  
+
*<math>KnownXArray</math> is the set of independent data.
 +
**INTERCEPT(),returns the intercept of the linear regression line.
  
 
==Description==
 
==Description==
Line 16: Line 17:
 
*The slope is calculated by:<math> b=\frac{\sum_{i=1}^{n} {(x_{i}-\bar{x})(y_{i}-\bar{y})}} {\sum_{i=1}^{n}{(x_{i}-\bar{x})}^2}</math>.  
 
*The slope is calculated by:<math> b=\frac{\sum_{i=1}^{n} {(x_{i}-\bar{x})(y_{i}-\bar{y})}} {\sum_{i=1}^{n}{(x_{i}-\bar{x})}^2}</math>.  
 
*In this formula<math> \bar{x}</math> and<math> \bar{y}</math> are the sample means  AVERAGE of <math> x</math>  and <math> y </math>.  
 
*In this formula<math> \bar{x}</math> and<math> \bar{y}</math> are the sample means  AVERAGE of <math> x</math>  and <math> y </math>.  
*In <math>INTERCEPT(y,x)</math>, the arguments can be numbers, names, arrays, or references that contain numbers.
+
*In <math>INTERCEPT (KnownYArray,KnownXArray)</math>, the arguments can be numbers, names, arrays, or references that contain numbers.
 
* The arrays  values are  disregarded when it is contains text, logical values or empty cells.  
 
* The arrays  values are  disregarded when it is contains text, logical values or empty cells.  
 
*This function will return the result as error when any one of the argument is non-numeric or <math>x</math> and <math>y</math> is having different number of data points and there is no data.
 
*This function will return the result as error when any one of the argument is non-numeric or <math>x</math> and <math>y</math> is having different number of data points and there is no data.
 +
 +
==ZOS==
 +
*The syntax is to calculate intercept of the regression line in ZOS is <math>INTERCEPT (KnownYArray,KnownXArray)</math>.
 +
**<math>KnownYArray</math> is the set of dependent data
 +
**<math>KnownXArray</math> is the set of independent data.
 +
*For e.g.,intercept([14,16,19,15.25],[20.1,26,10,26.4])
 +
{{#ev:youtube|ltc2nl-pwpk|280|center|Intercept}}
  
 
==Examples==
 
==Examples==
DATA1        DATA2
 
  4                  12
 
  5                  20
 
  2                  15
 
10                    11
 
 
INTERCEPT(B5:B8,C5:C8)=10.13265306
 
 
DATA1          DATA2
 
    25                10
 
    -12                15 
 
      -9              -40
 
    30                52
 
    18                36
 
 
INTERCEPT(A2:A6,B2:B6)=4.754939085
 
 
 
 
{| class="wikitable"
 
{| class="wikitable"
 
|+Spreadsheet
 
|+Spreadsheet
Line 54: Line 44:
 
|-
 
|-
 
! 4
 
! 4
| 10 ||15  || -40  ||52 ||36||
+
| 10 ||15  || -40  ||52 ||36
|-
 
! 5
 
|  ||  ||  || ||
 
 
|}
 
|}
 +
 +
#=INTERCEPT(A1:D1,A2:D2)= 10.13265306
 +
#=INTERCEPT(A3:E3,A4:E4)= 4.754939085
 +
 +
==Related Videos==
 +
 +
{{#ev:youtube|LNSB0N6esPU|280|center|INTERCEPTS}}
 +
 +
==See Also==
 +
*[[Manuals/calci/PEARSON  | PEARSON ]]
 +
*[[Manuals/calci/AVERAGE  | AVERAGE ]]
 +
 +
==References==
 +
*[http://www.purplemath.com/modules/intrcept.htm INTERCEPT]
 +
 +
 +
 +
*[[Z_API_Functions | List of Main Z Functions]]
 +
 +
*[[ Z3 |  Z3 home ]]

Latest revision as of 16:04, 1 August 2018

INTERCEPT (KnownYArray,KnownXArray)


  • is the set of dependent data
  • is the set of independent data.
    • INTERCEPT(),returns the intercept of the linear regression line.

Description

  • This function is calculating the point where the line is intersecting y-axis using dependent and independent variables.
  • Using this function we can find the value of when is zero.
  • The intercept point is finding using simple linear regression.
  • It is fits a straight line through the set of points in such a way that makes vertical distances between the points of the data set and the fitted line as small as possible.
  • Regression methods nearly to the simple ordinary least squares also exist.
  • i.e.,The Least Squares method relies on taking partial derivatives with respect to the slope and intercept which provides a solvable pair of equations called normal equations.
  • Suppose there are data points , where
  • To find the equation of the regression line:.
  • This equation will give a "best" fit for the data points.
  • The "best" means least-squares method. Here b is the slope.
  • The slope is calculated by:.
  • In this formula and are the sample means AVERAGE of and .
  • In , the arguments can be numbers, names, arrays, or references that contain numbers.
  • The arrays values are disregarded when it is contains text, logical values or empty cells.
  • This function will return the result as error when any one of the argument is non-numeric or and is having different number of data points and there is no data.

ZOS

  • The syntax is to calculate intercept of the regression line in ZOS is .
    • is the set of dependent data
    • is the set of independent data.
  • For e.g.,intercept([14,16,19,15.25],[20.1,26,10,26.4])
Intercept

Examples

Spreadsheet
A B C D E
1 4 5 2 10
2 12 20 15 11
3 25 -12 -9 30 18
4 10 15 -40 52 36
  1. =INTERCEPT(A1:D1,A2:D2)= 10.13265306
  2. =INTERCEPT(A3:E3,A4:E4)= 4.754939085

Related Videos

INTERCEPTS

See Also

References