# 6. API Example¶

## 6.1. `rnorm`¶

reStructuredText:

```.. automodule:: statspy.basics
:members: rnorm
```

Results:

`statspy.basics.``rnorm`(n, mean=0, sd=1)[source]

Random generation for the normal distribution with mean equal to mean and standard deviation equation to sd same functions as rnorm in r: `rnorm(n, mean=0, sd=1)`

Parameters: n – the number of the observations mean – vector of means sd – vector of standard deviations the vector of the random numbers Wenqiang Feng von198@gmail.com

## 6.2. `dnorm`¶

reStructuredText:

```.. automodule:: statspy.basics
:members: dnorm
:noindex:
```

Results:

`statspy.basics.``dnorm`(x, mean=0, sd=1, log=False)[source]

Density of the normal distribution with mean equal to mean and standard deviation equation to sd same functions as rnorm in r: `dnorm(x, mean=0, sd=1, log=FALSE)`

Parameters: x – the vector od quantiles mean – vector of means sd – vector of standard deviations the list of the density Wenqiang Feng von198@gmail.com

## 6.3. `runif`¶

reStructuredText:

```.. automodule:: statspy.basics
:members: runif
:noindex:
```

Results:

`statspy.basics.``runif`(n, min=0, max=1)[source]

Random generation from the uniform distribution same functions as rnorm in r: `runif(n, min=0, max=1)`

Parameters: n – the number of the observations min – the lower limit of the distribution max – the upper limit of the distribution the list of n uniform random numers Wenqiang Feng von198@gmail.com

## 6.4. `T-test`¶

reStructuredText:

```.. automodule:: statspy.tests
:members:
```

Results:

`statspy.tests.``t_test`(x, y=None, mu=0.0, conf_level=0.95)[source]

Performs one and two sample t-tests on vectors of data.

same functions as t.test in r: `t.test(x, ...)`

`t.test(x, y = NULL,`

`alternative = c("two.sided", "less", "greater"),`

`mu = 0, paired = FALSE, var.equal = FALSE,`

`conf.level = 0.95, ...)`

Parameters: x – a (non-empty) numeric vector of data values. y – an optional (non-empty) numeric vector of data values. mu – vector of standard deviations. conf_level – confidence level of the interval. the vector of the random numbers. Wenqiang Feng von198@gmail.com