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.

Requirements

  • Access to a computer with internet connectivity.
  • A basic understanding of mathematics
  • including algebra and arithmetic.
  • Familiarity with fundamental concepts in data analysis and problem-solving.
  • A willingness to learn and engage with statistical concepts and Python programming.
  • Basic knowledge of Python is a plus but not mandatory.

Description

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.
Statistics and Hypothesis Testing for Data science

Course Includes:

  • Price: FREE
  • Enrolled: 26482 students
  • Language: English
  • Certificate: Yes
  • Difficulty: Advanced
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