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
Returns:

the vector of the random numbers
Author:

Wenqiang Feng
Email:

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
Returns:

the list of the density
Author:

Wenqiang Feng
Email:

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
Returns:

the list of n uniform random numers
Author:

Wenqiang Feng
Email:

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.
Returns:

the vector of the random numbers.
Author:

Wenqiang Feng
Email:

von198@gmail.com