Stats Package
A comprehensive Python package for statistical analysis, providing functions for hypothesis testing, confidence intervals, regression analysis, and more.
Features
- Descriptive Statistics: Basic statistics, z-score conversions, and percentile calculations
- Standard Error Calculations: For means, proportions, and their differences
- Critical Values: Calculate critical values for hypothesis testing
- Confidence Intervals: For means and proportions
- Sample Size Calculations: Determine required sample sizes for studies
- Hypothesis Testing: Single-sample and two-sample tests for means and proportions
- Regression Analysis: Linear regression with confidence intervals and predictions
- Probability Calculations: Central Limit Theorem applications
- Inverse Calculations: Solve for various statistical parameters
Installation
pip install stats211
Quick Start
from stats import *
# Hypothesis testing
test_mean(0, 3.1, 1.3, 18)
# Confidence intervals
ci_mean(3.1, 1.3, 18, 0.95)
# Two-sample tests
test_two_means(1610, 129.8, 18.906, 1929, 127.07, 21.975, equal_var=True, alpha=0.13)
# Sample size calculations
sample_size_mean(0.9, 11.71, 0.84)
# Get help
stats_help()
Module Organization
The package is organized into the following modules:
utils: Color printing and file I/O utilitiesdescriptive: Basic statistics and z-score conversionsstandard_error: Standard error calculationscritical_values: Critical value functionsconfidence_intervals: Confidence interval calculationssample_size: Sample size calculationshypothesis_testing: Single-sample hypothesis teststwo_sample: Two-sample hypothesis testsregression: Linear regression functionsprobability: Probability calculations (CLT)inverse: Inverse calculations
Usage Examples
Hypothesis Testing
from stats import test_mean, test_proportion
# Test a mean
test_mean(0, 3.1, 1.3, 18)
# Test a proportion
test_proportion(0.03, 0.04, 500, tail='right')
Confidence Intervals
from stats import ci_mean, ci_proportion
# Confidence interval for mean
ci_mean(3.1, 1.3, 18, 0.95)
# Confidence interval for proportion
ci_proportion(0.5, 100, 0.95)
Two-Sample Tests
from stats import test_two_means, test_two_proportions
# Two-sample t-test
test_two_means(1610, 129.8, 18.906, 1929, 127.07, 21.975, equal_var=True, alpha=0.13)
# Two-sample proportion test
test_two_proportions(314, 59, 319, 101)
Regression Analysis
from stats import slope_test, linregress_ci
# Test slope
slope_test(1.57, 0.606, 170, 0.05, 'two')
# Confidence interval for regression
linregress_ci(slope, se_slope, n, confidence=0.95)
Requirements
- Python >= 3.8
- numpy >= 1.20.0
- pandas >= 1.3.0
- scipy >= 1.7.0
License
MIT License
Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
Author
Isaac Lagoy
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