Statistics and Hypothesis Testing for Data science

Statistics and Hypothesis Testing for Data science, available at $19.99, has an average rating of 4.45, with 31 lectures, 5 quizzes, based on 254 reviews, and has 22171 subscribers.

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

Enroll now: Statistics and Hypothesis Testing for Data science

Summary

Title: Statistics and Hypothesis Testing for Data science

Price: $19.99

Average Rating: 4.45

Number of Lectures: 31

Number of Quizzes: 5

Number of Published Lectures: 31

Number of Published Quizzes: 5

Number of Curriculum Items: 36

Number of Published Curriculum Objects: 36

Original Price: $19.99

Quality Status: approved

Status: Live

What You Will 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.

Who Should Attend

• 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.

Target Audiences

• 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.