Statistics and Hypothesis Testing for Data science

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

[Free Udemy Course] Statistics and Hypothesis Testing for 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.

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