Statistical Tests in Python | NumPy, SciPy, Pandas & Statsmodels Tutorial
In this video, we learn how to perform real-world statistical analysis in Python using NumPy, SciPy, Pandas, and Statsmodels. This practical tutorial covers some of the most important statistical tests used in data science, bioinformatics, machine learning, and research analysis.
Topics covered in this tutorial:
• NumPy basics for statistical computing
• DataFrame making with Pandas
• Statistical testing using SciPy and Statsmodels
• Chi-Square Test (χ² Test)
• T-Test
• ANOVA (Analysis of Variance)
• Correlation analysis and p-values
Libraries used:
• NumPy
• Pandas
• SciPy
• Statsmodels
• Matplotlib
This tutorial is designed for beginners and intermediate learners who want to build strong foundations in statistical analysis using Python.
Useful for:
• Data Science
• Bioinformatics
• Medical Data Analysis
• Machine Learning
• Research Projects
• Academic Statistics
• Python for Data Analysis
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