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.

What you’ll learn

  • Fundamental concepts and importance of statistics in various fields..
  • How to use statistics for effective data analysis and decision-making..
  • Introduction to Python for statistical analysis, including data manipulation and visualization..
  • Different types of data and their significance in statistical analysis..
  • Measures of central tendency, spread, dependence, shape, and position..
  • How to calculate and interpret standard scores and probabilities..
  • Key concepts in probability theory, set theory, and conditional probability..
  • Understanding Bayes’ Theorem and its applications..
  • Permutations, combinations, and their role in solving real-world problems..
  • Practical knowledge of various statistical tests, including t-tests, chi-squared tests, and ANOVA, for hypothesis testing and inference..

Course Content

  • Introduction to Statistics –> 3 lectures • 17min.
  • Introduction to Descriptive Statistics –> 6 lectures • 39min.
  • Introduction to Basic and Conditional Probability –> 7 lectures • 59min.
  • Introduction to Inferential Statistics –> 10 lectures • 1hr 40min.
  • Introduction to Hypothesis Testing –> 5 lectures • 41min.

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Requirements

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!