Difference between revisions of "Manuals/calci/ZTEST"
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(Created page with "<div id="6SpaceContent" class="zcontent" align="left"> <font color="#484848"><font face="Arial, sans-serif"><font size="2">'''ZTEST'''</font></font></font><font color="#48484...") |
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− | <div | + | <div style="font-size:30px">'''ZTEST(ar,x,sigma)'''</div><br/> |
+ | *<math>ar</math> is the array of values. | ||
+ | *<math>x</math> is the value to test. | ||
+ | *<math>sigma</math> 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 <math>ZTEST(ar,x,sigma)</math>,<math> ar </math> is the array of values against which the hypothesized sample mean is to be tested. | |
− | + | *<math> x </math> is the hypothesized sample mean, and <math>sigma</math> 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 : <math>ZTEST(ar,\mu_0,sigma)=1-NORMSDIST((\bar{x}-μ0)/\frac{sigma}{\sqrt{n}}</math>. |
− | + | *ZTEST is calculated when sigma is omitted and x=μ0: | |
− | + | <math> ZTEST(ar,μ0)=1-NORMSDIST(\bar{x}-μ0)/\frac{s}{\sqrt{n}}</math> | |
− | + | where <math>bar{x}</math> is sample mean , <math> s</math> is the sample deviation and <math>n</math> 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: <math>2*MIN(ZTEST(ar,\mu_0,sigma),1-ZTEST(ar,\mu_0,sigma))</math>. | |
− | + | *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. | |
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Revision as of 22:39, 9 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.