Statistics and Hypothesis Testing for Data science

“Mastering Data Analysis and Making Informed Decisions with Statistical Hypothesis Testing in 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!

Who this course is for:

  • Students or professionals in various fields, including business, science, social sciences, and healthcare, who want to enhance their data analysis skills.
  • Data analysts, researchers, and scientists seeking to strengthen their statistical foundations and Python programming skills.
  • Anyone interested in gaining a deeper understanding of statistical concepts and their practical applications.
  • Beginners with no prior statistical knowledge but with a curiosity to learn and apply statistical methods.
  • Professionals looking to advance their career by acquiring valuable statistical and data analysis skills.
  • Individuals preparing for standardized tests or exams that include statistical and data analysis components.

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