Metadata-Version: 2.1
Name: applied_stats
Version: 0.0.3
Summary: A basic statistics module to compute MLEs / probabilities
Home-page: https://github.com/WillTirone/applied_stats
Author: William Tirone
Author-email: will.tirone1@gmail.com
License: UNKNOWN
Description: # Statistics_Module
        Creating a project to implement various statistical distributions and methods in Python.
        
        To install and run this project, do the following:
        1. Run the following to install: 
        
        ``` 
        pip install applied-stats
        ```
        
        2. Follow these examples to start plotting and calculating probabilities. The examples below, and several others, can also be found in the  [Demonstration Jupyter Notebook](https://github.com/WillTirone/applied-stats_examples/blob/main/Demonstration.ipynb)
        
        3. To run the test file, from the command line enter: ```python test.py```
        
        ## Usage
        
        ### To generate some plots and calculate some probabilities: 
        
        ```python
        >>> from applied_stats import continuous_distributions
        >>> a = Norm_rv(0,1)
        >>> a.plot_pdf()
        >>> a.probability_calc()
        ```
        ![link](https://github.com/WillTirone/applied_stats/blob/main/output_images/N(0%2C1)_plot.png)
        
        ```python
        >>> q = ChiSq_rv(4,crit_value=7)
        >>> q.plot_pdf(cv_probability=True)
        >>> q.probability_calc()
        ```
        ![link](https://github.com/WillTirone/applied_stats/blob/main/output_images/X-sqr(4).png)
        
        ### To calculate the numeric MLE of several common distributions: 
        
        ```python 
        >>> from stats_tools import mle 
        >>> a = [1,3,2,5,6,7,2,3,4,5]
        >>> mle.binomial(a)
        >>> 3.8
        
        >>> b = [1.2,4.3,2.3,6.8,2.4,3.6]
        >>> mle.exponential(b) 
        >>> 3.4333333333333336
        ```
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: Topic :: Scientific/Engineering :: Mathematics
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Operating System :: OS Independent
Description-Content-Type: text/markdown
