Difference between revisions of "Manuals/calci/ZTEST"

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     2. ar or x is empty.
 
     2. ar or x is empty.
 
     3. ar contains only one value.
 
     3. ar contains only one value.
 +
 +
==Examples==
 +
#'''Example 1'''
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{| class="wikitable"
 +
|+Spreadsheet
 +
|-
 +
! !! A !! B !! C !! D !! E !! F !! G
 +
|-
 +
! 1
 +
| 10 || 15 || 7 || 2 || 19 || 20 || 12
 +
|-
 +
! 2
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| 3 || 4 || 8 || 1 || 10 || 15
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|}
 +
1.ZTEST(A1:G1,4) = 0.00042944272036
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2.2*MIN(ZTEST(A1:G1,4),1-ZTEST(A1:G1,4)) = 0.000858885440
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3.ZTEST(A2:F2,10) = 0.9323691845
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4.2*MIN(ZTEST(A2:F2,10),1-ZTEST(A2:F2,10)) = 0.135261630850
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 +
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==See Also==
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*[[Manuals/calci/NORMDIST  | NORMDIST ]]
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*[[Manuals/calci/NORMINV  | NORMINV ]]
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*[[Manuals/calci/NORMSDIST  | NORMSDIST ]]
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*[[Manuals/calci/NORMSINV  | NORMSINV ]]
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*[[Manuals/calci/STANDARDIZE  | STANDARDIZE ]]
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 +
 +
==References==

Revision as of 00:15, 10 February 2014

ZTEST(ar,x,sigma)


  • is the array of values.
  • is the value to test.
  • is the standard deviation of the population.


Description

  • This function gives the one-tailed probability of z-test.
  • Z-test is used to determine whether two population means are different when the variances are known and the sample size is large.
  • In , is the array of values against which the hypothesized sample mean is to be tested.
  • is the hypothesized sample mean, and is the standard deviation of the population.
  • When we are not giving the sigma value, it will use the standard deviation of sample.
  • This function returns the probability that the supplied hypothesized sample mean is greater than the mean of the supplied data values.
  • The test statistic should follow a normal distribution.
  • ZTEST is calculated when sigma is not omitted and x=μ0 : Failed to parse (syntax error): {\displaystyle ZTEST(ar,\mu_0,sigma)=1-NORMSDIST((\bar{x}-μ0)/\frac{sigma}{\sqrt{n}})} .
  • ZTEST is calculated when sigma is omitted and x=μ0:

Failed to parse (syntax error): {\displaystyle ZTEST(ar,μ0)=1-NORMSDIST((\bar{x}-μ0)/\frac{s}{\sqrt{n}})} where is sample mean , is the sample deviation and is the size of the sample.

  • Suppose we want to calculate the z-test for two tailed probability then this can be done by using the Z_test function: .
  • This function will give the result as error when
    1. Any one of the argument is non-numeric.
    2. ar or x is empty.
    3. ar contains only one value.

Examples

  1. Example 1
Spreadsheet
A B C D E F G
1 10 15 7 2 19 20 12
2 3 4 8 1 10 15

1.ZTEST(A1:G1,4) = 0.00042944272036 2.2*MIN(ZTEST(A1:G1,4),1-ZTEST(A1:G1,4)) = 0.000858885440 3.ZTEST(A2:F2,10) = 0.9323691845 4.2*MIN(ZTEST(A2:F2,10),1-ZTEST(A2:F2,10)) = 0.135261630850


See Also


References