Fundamentals of statistics

This repository collects jupyter notebooks, often very short, illustrating fundamental facts and concepts in probability theory and statistics.

Topics currently include:

probability functions (PDF, CDF, etc.)
linear regression
classification with logisitic regression (with visualization using "fuzzy" decision boundaries)
bootstrapping
error bars
hypothesis testing (Student's t-test, Welch's t-test) and p-values

Name		Name	Last commit message	Last commit date
Latest commit History 6 Commits
8000 README.md		README.md
bootstrapping.ipynb		bootstrapping.ipynb
chi-squared-distribution.ipynb		chi-squared-distribution.ipynb
continuous-probability-functions.ipynb		continuous-probability-functions.ipynb
distribution-of-p-values.ipynb		distribution-of-p-values.ipynb
error-bars-in-statistics.ipynb		error-bars-in-statistics.ipynb
exam-scores.csv		exam-scores.csv
histograms-with-numpy.ipynb		histograms-with-numpy.ipynb
independent-t-tests.ipynb		independent-t-tests.ipynb
iris-dataset-statistics.ipynb		iris-dataset-statistics.ipynb
linear-regression.ipynb		linear-regression.ipynb
logistic-regression-with-the-iris-dataset.ipynb		logistic-regression-with-the-iris-dataset.ipynb
logistic-regression.ipynb		logistic-regression.ipynb
one-sample-t-test.ipynb		one-sample-t-test.ipynb
paired-t-tests.ipynb		paired-t-tests.ipynb
standard-deviations-standard-error.ipynb		standard-deviations-standard-error.ipynb
two-independent-unequal-variance-welch-t-test-duke-crabs.ipynb		two-independent-unequal-variance-welch-t-test-duke-crabs.ipynb
type-I-and-II-errors.ipynb		type-I-and-II-errors.ipynb

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