Metadata-Version: 2.1
Name: gauss_binom_test
Version: 0.2.4
Summary: Gaussian and Binomial distributions
Home-page: UNKNOWN
Author: ludovico
License: MIT
Description: # Gaussian and Binomial Distributions
        
        A basic package for calculating and visualizing Gaussian and Binomial Distributions.
        This is only a test.
        
        
        # How to import the classes using the interpret
        
        ```console 
        $ python
        >>> from gauss_binom_test import Gaussian, Binomial
        ```
        
        # Features
        
        - Calculate the Gaussian and Binomial pdf of a data set
        - Calculate the mean and standard deviation
        - Calculate the sum of two pdfs
        - Plot the histogram of data points and normalizdd histogram of the pdf
        
        
        
        # Example
        
        Open the Python interpreter:
        
        **Create a standard normalmdistribution (zero mean and standard deviation equal to one)**
        
        ```console
        >>> gaussian_normal = Gaussian()
        >>> gaussian_normal
        mean 0, standard deviation 1
        ```
        
        **Create a Gaussian distribution with mean=5 and stdv=2**
        
        ```console
        >>> gaussian_one = Gaussian(5,2)
        mean 5, standard deviation 2
        ```
        
        **Addition of two Gaussian distributions**
        
        ```console
        >>> gaussian_sum = gaussian_normal + gaussian_one
        >>> gaussian_sum.mean()
        5
        >>> sample stdev
        >>> gaussian_sum.stdev()
        2.2360679
        ```
        
        **Addition of three Gaussian distributions**
        
        ```console
        >>> gaussian_sum = Gaussian(1,2) + Gaussian(2,3) + Gaussian(3,4)
        >>> gaussian_sum
        >>> mean 6, standard deviation 5.3851648
        ```
        
        **Calculate the value of the Gaussian distribution function at a given point **
        
        ```console
        >>> gaussian_one = Gaussian(5,2)
        >>> gaussian_one.pdf(6)
        0.17603266338
        ```
        
        **Generate a Binomial distribution of 20 trials and 0.5 probability of an event occurring**
        
        ```console
        >>> binom_one = Binomial(.5, 20)
        >>> binom_one
        mean 10.0, standard deviation 2.23606797749979, p 0.5, n 20
        ```
        
        **Calculate the probability of occurring 5 successes for a Binomial distribution of 20 trials and p=0.5**
        
        ```console
        >>> Binomial(.5, 20).pdf(5)
        0.0147857666015625
        ```
        
        **Adding two binomial distributions**
        
        ```console
        >>> binom_sum = Binomial(.5, 20) + Binomial(.5, 10)
        mean 15.0, standard deviation 2.7386127875258306, p 0.5, n 30
        ```
        
        
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Requires-Python: >=3.6
Description-Content-Type: text/markdown
