Difference between revisions of "Manuals/calci/ZTEST"
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*This function returns the probability that the supplied hypothesized sample mean is greater than the mean of the supplied data values. | *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. | *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 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: | *ZTEST is calculated when sigma is omitted and x=μ0: | ||
− | <math> ZTEST(ar,μ0)=1-NORMSDIST(\bar{x}-μ0)/\frac{s}{\sqrt{n}}</math> | + | <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. | 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>. | *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>. |
Revision as of 22:43, 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 (MathML with SVG or PNG fallback (recommended for modern browsers and accessibility tools): Invalid response ("Math extension cannot connect to Restbase.") from server "https://wikimedia.org/api/rest_v1/":): {\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.