Statify (for STAT 101)

📗 WORK IN PROGRESS

Introduction

Welcome to Statify, a personal project aimed at providing a comprehensive set of statistical functions and tools for Stat 101. This repository is currently a work in progress, and I plan to develop it further into a pip module in the future. Here, you will find a collection of functions that I have learned in my Statistics class and found useful.

Functions

Probability Distributions

Normal Distribution

• Normal CDF: Compute the cumulative distribution function (CDF) of a normal distribution.
• Normal PDF: Calculate the probability density function (PDF) of a normal distribution.

Binomial Distribution

• Binomial CDF: Calculate the cumulative distribution function (CDF) of a binomial distribution.
• Binomial PDF: Compute the probability mass function (PMF) of a binomial distribution.

t-Distribution

• t CDF: Compute the cumulative distribution function (CDF) of a t-distribution.
• t PDF: Calculate the probability density function (PDF) of a t-distribution.

Inverse Functions

• Inv Norm: Calculate the inverse of the normal distribution.
• Inv T: Compute the inverse of the t-distribution.

Regression Analysis

• Linear Regression: Perform linear regression analysis on a given dataset.

Descriptive Statistics

• Quartiles: Calculate the quartiles of a dataset.
• Five Value Summary: Compute the minimum, first quartile, median, third quartile, and maximum values of a dataset.

Data Visualization

• Histogram: Generate a histogram to visualize the distribution of a dataset.
• Scatter Plot: Create a scatter plot to explore the relationship between two variables.
• Dot Plot: Generate a dot plot to visualize the distribution of a dataset.
• Box-Whisker Plot: Generate a box-whisker plot to visualize the distribution of a dataset.

Analysis of Variance (ANOVA)

• Anova Table: Perform an analysis of variance (ANOVA) and generate an ANOVA table.

Future Add Ons

In addition to the current functions, I have exciting plans for future expansions of Statify. Here are some features I am considering:

1. One-sided and Two-sided Tests: Include functions for conducting one-sided and two-sided hypothesis tests.
2. Additional Probability Distributions: Add support for Poisson, Hypergeometric, and other probability distributions.
3. Archive Dumping: Implement a feature to allow dumping and archiving of statistical data for future reference.
4. Rejection Region and p-value Tests: Develop functions for calculating rejection regions and p-values for hypothesis testing.
5. Expected Value and Variance: Include functions to calculate the expected value (E(x)) and variance (V(x)) for various probability distributions.
6. Sampling: Introduce functions for sampling from different distributions to facilitate simulation and inference.