GitHub - ritika-thakur/Statistics-Probability-Programming: This repository is the practical implementation and study of the statistics and probability via programming, which is essential for Machine learning.

ritika-thakur / Statistics-Probability-Programming Public

This repository is the practical implementation and study of the statistics and probability via programming, which is essential for Machine learning.

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Name		Name	Last commit message	Last commit date
Latest commit History 23 Commits
.ipynb_checkpoints		.ipynb_checkpoints
Goodness-of-fit-test		Goodness-of-fit-test
Hypothesis_Testing		Hypothesis_Testing
One-Way-Annova		One-Way-Annova
Pearson-Correlation-Test		Pearson-Correlation-Test
Two-way-annova		Two-way-annova
Conditional-and-joint-probability-1.ipynb		Conditional-and-joint-probability-1.ipynb
Confidence-Intervals.ipynb		Confidence-Intervals.ipynb
Demonstration-of-CLT-for-normal-distribution.ipynb		Demonstration-of-CLT-for-normal-distribution.ipynb
Demonstration-of-CLT.ipynb		Demonstration-of-CLT.ipynb
Demonstration-of-covariance.ipynb		Demonstration-of-covariance.ipynb
Diff-btw-samples-withdrawn-from-2-populations.ipynb		Diff-btw-samples-withdrawn-from-2-populations.ipynb
Large-Sample-Domain-Demo-for-diff-distributions.ipynb		Large-Sample-Domain-Demo-for-diff-distributions.ipynb
Normal-and-Poisson-Probability-Distribution.ipynb		Normal-and-Poisson-Probability-Distribution.ipynb
Practical-Definition-Of-Probability.ipynb		Practical-Definition-Of-Probability.ipynb
Sampling-distribution-and-CLT.ipynb		Sampling-distribution-and-CLT.ipynb
data.csv		data.csv