Difference between revisions of "Manuals/calci/TTESTEQUALVARIANCES"

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(Created page with "<div id="6SpaceContent" class="zcontent" align="left"> '''TTESTTWOSAMPLESEQUALVARIANCES('''Array1, Array2, HypothesizeDiff, Alpha, NewTableFlag) where, '''Array1 '''...")
 
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<div id="6SpaceContent" class="zcontent" align="left">
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<div style="font-size:30px">'''TTESTTWOSAMPLESEQUALVARIANCES(ar1,ar2,md,alpha,lv)'''</div><br/>
 +
*<math>ar1 </math> and <math> ar2 </math>  are set of values.
 +
*<math>md </math> is the  Hypothesized Mean Difference.
 +
*<math> alpha </math> is the significance level.
 +
*<math> lv </math> is the logical value.
  
'''TTESTTWOSAMPLESEQUALVARIANCES('''Array1, Array2, HypothesizeDiff, Alpha, NewTableFlag)
 
  
where,
+
==Description==
 +
*This function calculating the two Sample for equal variances determines whether two sample means are equal.
 +
*We can use this test when both:
 +
*1.the two sample sizes  are equal;
 +
*2.it can be assumed that the two distributions have the same variance.
 +
*In TTESTTWOSAMPLESEQUALVARIANCES(ar1,ar2,md,alpha,lv), ar1 and ar2 are two arrays of sample values.md is the Hypothesized Mean Difference .
 +
*Suppose md=0 which  indicates that sample means are hypothesized to be equal.
 +
*alpha is the significance level which ranges from 0 to1.
 +
*lv is the logical value like TRUE or FALSE.
 +
*TRUE is indicating the result will display in new worksheet.Suppose we are omitted the lv value it will consider the value as FALSE.
 +
*The t statistic of this function calculated by:
 +
<math>t = \frac{\bar{x_1}-\bar{x_2}}{s_x_1.s_x_2.\sqrt\frac{2}{n}}</math> ,where <math>s_x_1.s_x_2 = \sqrt\frac{1}{2}(s_x_1^2+s_x_2^2)</math>.
 +
*Here <math>s_x_1</math> and <math>s_x_2</math> are unbiased estimators of the variances of two samples.<math>s_x_1.s_x_2</math> is the grand standard deviation data 1 and data2 and n is the data points of two data set. 
 +
*This function will give the result as error when
 +
  1.any one of the argument is nonnumeric.
 +
  2.alpha>1
 +
  3.ar1 and ar2 are having different number of data points.
  
'''Array1 '''- Input range should be one block.
 
  
'''Array2 '''- Input range should be one block.
+
==Examples==
 
+
{| class="wikitable"
'''HypothesizeDiff '''- represents the Hypothesized Mean Difference.A value 0 indicates that sample means are hypothesized to be equal.
+
|+Spreadsheet
 
+
|-
'''Alpha '''- represents the significance level and value in range 0 to 1.
+
! !! A !! B !! C !! D!! E !! F
 +
|-
 +
! 1
 +
| 10 || 15 || 18 || 27 || 12 || 34
 +
|-
 +
! 2
 +
| 17 || 20 || 25 || 39 || 9 || 14
 +
|}
  
''' ''''''NewTableFlag''' - is the TRUE or FALSE.If set as TRUE,the result in new sheet. If NewTableFlag is omitted, it assumed to be FALSE.</div>
 
----
 
<div id="1SpaceContent" class="zcontent" align="left">T-Test: Two Sample for equal variances determines whether two sample means are equal.</div>
 
----
 
<div id="7SpaceContent" class="zcontent" align="left">
 
  
Lets see an example in (Column3Row1)
 
  
<nowiki>=TTESTTWOSAMPLESEQUALVARIANCES (R1C1:R6C1, R1C2:R6C2, 0, 0.05, TRUE)</nowiki>
+
#=TTESTSAMPLESEQUALVARIANCE(A1:F1,A2:F2,0.5)
  
TTESTTWOSAMPLESEQUALVARIANCES returns the result in new sheet(9Space).
 
  
<nowiki>=TTESTTWOSAMPLESEQUALVARIANCES(R1C1:R4C1,R1C2:R6C2, 0, 0.055, TRUE)</nowiki>
 
  
TTESTTWOSAMPLESEQUALVARIANCES returns the #ERROR(LengthofArray1 != LengthofArray2).
+
==See Also==
 +
*[[Manuals/calci/TTEST  | TTEST ]]
 +
*[[Manuals/calci/TDIST  | TDIST ]]
 +
*[[Manuals/calci/TINV  | TINV ]]
 +
*[[Manuals/calci/TTESTUNEQUALVARIANCES  | TTESTUNEQUALVARIANCES ]]
  
</div>
 
----
 
<div id="12SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="left">
 
 
T-TEST : TWO SAMPLE ASSUMING EQUAL VARIANCES
 
 
</div></div>
 
----
 
<div id="10SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Syntax </div><div class="ZEditBox"><center></center></div></div>
 
----
 
<div id="4SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Remarks </div></div>
 
----
 
<div id="3SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Examples </div></div>
 
----
 
<div id="11SpaceContent" class="zcontent" align="left"><div class="ZEditBox" align="justify">Description </div></div>
 
----
 
<div id="8SpaceContent" class="zcontent" align="left">
 
 
If the Alpha &lt; 0 or Alpha &gt;1, TTESTTWOSAMPLESEQUALVARIANCES returns the #ERROR.
 
 
TTESTTWOSAMPLESEQUALVARIANCES returns the #ERROR, if Length of Array1 != Length of Array2.
 
 
</div>
 
----
 
<div id="2SpaceContent" class="zcontent" align="left">
 
 
{| id="TABLE3" class="SpreadSheet blue"
 
|- class="even"
 
| class=" " |
 
| Column1
 
| Column2
 
| class="  " | Column3
 
| Column4
 
|- class="odd"
 
| class=" " | Row1
 
| 10
 
| 3
 
| class="sshl_f" | 9Space
 
| class=" " |
 
|- class="even"
 
| class="  " | Row2
 
| 7
 
| 8
 
| class="    " |
 
| class=" " |
 
|- class="odd"
 
| Row3
 
| 12
 
| 8
 
| class=" " |
 
| class=" " |
 
|- class="even"
 
| Row4
 
| 17
 
| 18
 
| class="sshl_f" | #ERROR
 
| class=" " |
 
|- class="odd"
 
| class=" " | Row5
 
| class=" " | 46
 
| 34
 
| class="          " |
 
| class=" " |
 
|- class="even"
 
| Row6
 
| class="SelectTD1" | 6
 
| 7
 
| class=" " |
 
| class=" " |
 
|}
 
 
<div align="left">[[Image:calci1.gif]]</div></div>
 
----
 
<div id="9SpaceContent" class="zcontent" align="left">
 
 
{| class="SpreadSheet blue"
 
|+ t-Test: Two-Sample Assuming Equal Variances<br />
 
|- class="even"
 
!
 
! Variable1
 
! Variable2
 
|- class="odd"
 
| Mean
 
| 16.333333333333332
 
| 13
 
|- class="even"
 
| Variance
 
| 226.66666666666668
 
| 130.4
 
|- class="odd"
 
| Observations
 
| 6
 
| 6
 
|- class="even"
 
| Pooled Variance
 
| 178.53333333333336
 
|- class="odd"
 
| Hypothesized Mean Difference
 
| 0
 
|- class="even"
 
| Degree Of Freedom
 
| 10
 
|- class="odd"
 
| T Statistics
 
| 0.4320954725359997
 
|- class="even"
 
| P(T&lt;=t) One-tail
 
| 0.3374203531947199
 
|- class="odd"
 
| T Critical One-tail
 
| 1.8124611201453893
 
|- class="even"
 
| P(T&lt;=t) Two-tail
 
| 0.6748407063894398
 
|- class="odd"
 
| T Critical Two-tail
 
| 2.2281388448257084
 
|}
 
  
</div>
+
==References==
----
 

Revision as of 03:11, 3 February 2014

TTESTTWOSAMPLESEQUALVARIANCES(ar1,ar2,md,alpha,lv)


  • and are set of values.
  • is the Hypothesized Mean Difference.
  • is the significance level.
  • is the logical value.


Description

  • This function calculating the two Sample for equal variances determines whether two sample means are equal.
  • We can use this test when both:
  • 1.the two sample sizes are equal;
  • 2.it can be assumed that the two distributions have the same variance.
  • In TTESTTWOSAMPLESEQUALVARIANCES(ar1,ar2,md,alpha,lv), ar1 and ar2 are two arrays of sample values.md is the Hypothesized Mean Difference .
  • Suppose md=0 which indicates that sample means are hypothesized to be equal.
  • alpha is the significance level which ranges from 0 to1.
  • lv is the logical value like TRUE or FALSE.
  • TRUE is indicating the result will display in new worksheet.Suppose we are omitted the lv value it will consider the value as FALSE.
  • The t statistic of this function calculated by:
Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. TeX parse error: Double subscripts: use braces to clarify"): {\displaystyle t={\frac {{\bar {x_{1}}}-{\bar {x_{2}}}}{s_{x}_{1}.s_{x}_{2}.{\sqrt {\frac {2}{n}}}}}}
 ,where Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. TeX parse error: Double subscripts: use braces to clarify"): {\displaystyle s_{x}_{1}.s_{x}_{2}={\sqrt {\frac {1}{2}}}(s_{x}_{1}^{2}+s_{x}_{2}^{2})}
.
  • Here Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. TeX parse error: Double subscripts: use braces to clarify"): {\displaystyle s_{x}_{1}} and Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. TeX parse error: Double subscripts: use braces to clarify"): {\displaystyle s_{x}_{2}} are unbiased estimators of the variances of two samples.Failed to parse (Conversion error. Server ("https://wikimedia.org/api/rest_") reported: "Cannot get mml. TeX parse error: Double subscripts: use braces to clarify"): {\displaystyle s_{x}_{1}.s_{x}_{2}} is the grand standard deviation data 1 and data2 and n is the data points of two data set.
  • This function will give the result as error when
  1.any one of the argument is nonnumeric.
  2.alpha>1
  3.ar1 and ar2 are having different number of data points.


Examples

Spreadsheet
A B C D E F
1 10 15 18 27 12 34
2 17 20 25 39 9 14


  1. =TTESTSAMPLESEQUALVARIANCE(A1:F1,A2:F2,0.5)


See Also


References