This repository contains PE.pdf, the PDF summarizing the entire content covered in a Probability and Statistics class.
- Basic probability concepts: random experiments, sample space, events, and conditional probability.
- Discrete and continuous random variables: definitions, distribution functions, and common probability distributions.
- Joint, marginal, and conditional distributions for random pairs, along with concepts of independence, covariance, and correlation.
- Linear combinations of random variables and the central limit theorem.
- Point estimation using the maximum likelihood estimation method.
- Interval estimation with confidence intervals for expected value, variance, and probability of success.
- Hypothesis testing for expected value, variance, and probability of success, including Pearson's chi-square goodness-of-fit test.
- Introduction to simple linear regression, inference about regression line parameters, and coefficient of determination.
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Contributions to this repository are welcome! If you notice any errors or have suggestions for improvements or updates on the course's contents, feel free to open an issue or submit a pull request.