This course will introduce you to the analysis and visualization of quantitative data. After completion of this course, you will be able to:
- Summarize quantitative datasets using descriptive statistics to extract key aspects and insights
- Compose accurate and beautiful graphical displays of quantitative information to effectively convey the insights gained from data
- Analyze and visualize relationships between different variables
- Determine and communicate how certain you are of your data analysis conclusions
- Recognize and avoid common pitfalls and errors in data analysis
- Use the R language for statistical computing
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The course will cover the following topics:
- Quantitative data, categorical data, and summary statistics
- Data display and visualization
- The R language for statistical computing
- Estimation and uncertainty
- Hypothesis testing
- Quantifying relationships between variables
- Information and entropy
You will not need to buy any books for following this course. As a reference for the R programming language, we will use the book "R for Data Science" by Hadley Wickham, which is freely available online: https://r4ds.had.co.nz. If you would like to know more about data visualization beyond what we cover in this course, we recommend the book "The Visual Display of Quantitative Information" by Edward Tufte.
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