# Hypothesis Testing (T Test » Single Sample) (G Dataflow)

Tests hypotheses about the mean of a population whose distribution is at least approximately normal but whose variance is unknown.

## sample set

Randomly sampled data from the population.

## mean

Hypothesized mean of the population.

The null hypothesis is that the population mean is equal to mean.

Default: 0

## significance level

Probability that this node incorrectly rejects a true null hypothesis.

Default: 0.05

## error in

Error conditions that occur before this node runs.

The node responds to this input according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error error in contains an error
If no error occurred before the node runs, the node begins execution normally.

If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Default: No error

## alternative hypothesis

Hypothesis to accept if this node rejects the null hypothesis that the population mean is equal to mean.

Name Value Description
mean(pop) != mean 0 The population mean is not equal to mean.
mean(pop) > mean 1 The population mean is greater than mean.
mean(pop) < mean -1 The population mean is less than mean.

Default: mean(pop) != mean

## null hypothesis rejected?

A Boolean that indicates whether this node rejects the null hypothesis.

 True p value is less than or equal to significance level. This node rejects the null hypothesis and accepts the alternative hypothesis. False p value is greater than significance level. This node accepts the null hypothesis and rejects the alternative hypothesis.

## p value

Smallest significance level that leads to rejection of the null hypothesis based on the sample sets.

## confidence interval

Lower and upper limits for the population mean. confidence interval indicates the uncertainty in the estimate of the true population mean.

### low

Lower limit of the estimate of the population mean.

### high

Upper limit of the estimate of the population mean.

## t test information

Sample statistics of the Student's t test.

### sample mean

Mean of sample set.

### sample standard deviation

Standard deviation of sample set.

### sample standard error mean

Standard error of the mean of sample set.

### degree of freedom

Degree of freedom of the Student's t distribution that the test statistic follows.

### sample t value

Sample test statistic used in the Student's t test.

sample t value is equal to $\frac{\mathrm{sample mean}\text{\hspace{0.17em}}-\text{\hspace{0.17em}}\mathrm{mean}}{\mathrm{sample standard error mean}}$.

### t critical value

Student's t value that corresponds to significance level and alternative hypothesis.

Algorithm for Calculating t critical value

Let Tn represent a student's t distributed variate with n degrees of freedom. t critical value satisfies the following equations based on the value of alternative hypothesis.

alternative hypothesis t critical value
mean(pop) != mean Prob{Tn > t critical value} = significance level / 2
mean(pop) > mean Prob{Tn > t critical value} = significance level
mean(pop) < mean Prob{Tn > t critical value} = significance level

## error out

Error information.

The node produces this output according to standard error behavior.

Standard Error Behavior

Many nodes provide an error in input and an error out output so that the node can respond to and communicate errors that occur while code is running. The value of error in specifies whether an error occurred before the node runs. Most nodes respond to values of error in in a standard, predictable way.

error in does not contain an error error in contains an error
If no error occurred before the node runs, the node begins execution normally.

If no error occurs while the node runs, it returns no error. If an error does occur while the node runs, it returns that error information as error out.

If an error occurred before the node runs, the node does not execute. Instead, it returns the error in value as error out.

Where This Node Can Run:

Desktop OS: Windows

FPGA: Not supported

Web Server: Not supported in VIs that run in a web application