Statistical Thinking in Python (Part 2)

Starting at USD 39.00
4 hours duration

Learn to perform the two key tasks in statistical inference: parameter estimation and hypothesis testing.

Upon completion of Statistical Thinking in Python (Part 1), participants will possess a probabilistic mindset and foundational skills in hacker statistics, enabling them to effectively analyze data sets and extract valuable insights. This course aims to further enhance and refine their hacker statistics toolkit, focusing on two crucial aspects of statistical inference: parameter estimation and hypothesis testing. Throughout the course, participants will engage with real-world data sets, culminating in the analysis of measurements pertaining to the renowned finches studied by Charles Darwin. By the end of this course, participants will have acquired new knowledge and extensive practical experience, equipping them to confidently tackle their own inference problems in real-world scenarios.

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DataCamp is an online learning platform that offers interactive courses and tutorials for data science and analytics. It provides a wide range of courses covering topics such as Python, R, SQL, machine learning, data visualization, and more. The platform offers a hands-on learning experience through coding exercises and projects, allowing users to practice and apply their skills in real-world scenarios. DataCamp also offers a personalized learning experience with adaptive learning technology that adjusts the course content based on the user's skill level and progress. It is widely used by individuals, professionals, and organizations to enhance their data science skills and stay up-to-date with the latest trends and technologies in the field.
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