Statistics and Hypothesis Testing for Data science

Welcome to "Data Science Essentials: Statistical Inference and Hypothesis Testing" – a comprehensive 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!