Statistics and Hypothesis Testing for Data science

Equip yourself with the essential Python skills required for effective data manipulation and visualization.

Learn to categorize data, setting the stage for meaningful analysis.

Discover how to summarize data with measures like mean, median, and mode.

Explore the variability in data using concepts like range, variance, and standard deviation.

Understand relationships between variables with correlation and covariance.

Grasp the shape and distribution of data using techniques like quartiles and percentiles.

Learn to standardize data and calculate z-scores.

Dive into probability theory and its practical applications.

Lay the foundation for probability calculations with set theory.

Explore the probability of events under certain conditions.

Uncover the power of Bayesian probability in real-world scenarios.

Solve complex counting problems with ease.

Understand the concept of random variables and their role in probability.

Explore various probability distributions and their applications.