Statistics and Hypothesis Testing for Data science

Welcome to “Statistics and Hypothesis Testing for Data Science” – a comprehensive Udemy course that will empower you with the essential statistical knowledge and data analysis skills needed for success in the world of data science.

Here’s what you’ll learn:

• Delve into the world of data-driven insights and discover how statistics plays a pivotal role in shaping our understanding of information.
• 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.

This course will empower you with the knowledge and skills needed to analyze data effectively, make informed decisions, and apply statistical methods in a data science context. Whether you’re a beginner or looking to deepen your statistical expertise, this course is your gateway to mastering statistics for data science. Enroll now and start your Journey!