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Basic Statistics in Python (ANOVA)
  • Level Beginner
  • Duration 4 hours
  • Offered by

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In this 1-hour long project-based course, you will learn how to set up a Google Colab notebook, source data from the internet, load data into Python, merge two datasets, clean data, perform exploratory data analysis, carry out ANOVA and create boxplots. Throughout the course you will work on an Education dataset from World Bank. This will allow you to perform statistical analysis on your own datasets in Python. This project does not require any previous Python or coding experience, but it would be useful for learners to understand the statistical methods covered. The course includes data sourcing and cleaning which are invaluable real world skills, and focuses on visualizing your results which is needed as a large part of any analysis is the storytelling.

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Unlock the fundamentals of statistical analysis with the "Basic Statistics in Python (ANOVA)" course, designed for beginners in the IT & Computer Science domain. Guided by Coursera, this engaging 1-hour project-based course provides a comprehensive introduction to essential data handling and analysis techniques using Python. Learn to set up a Google Colab notebook, source and load data from the internet, merge and clean datasets, and perform exploratory data analysis. The course emphasizes the practical application of ANOVA (Analysis of Variance) and the creation of boxplots, equipping you with critical skills for analyzing and visualizing data. Using a real-world Education dataset from the World Bank, you will gain hands-on experience in statistical analysis, making it easier to apply these techniques to your own datasets. No prior Python or coding experience is required, although a basic understanding of statistical methods will enhance your learning experience. With a duration of just 1 hour, this beginner-level course is available for free, making it an accessible and valuable resource for anyone looking to build a foundation in data analysis and storytelling through visualization. Whether you're a student, a professional looking to upskill, or simply curious about data science, this course offers the practical knowledge you need to get started.