Free online workbook, designed to be used alongside the CORE textbooks or as part of other courses. A succession of exercises are covered in R, Excel and Google Sheets. Screen-shots walk the reader through the steps of using each interface. The twelve chapters touch on topics including climate change, inequality, wellbeing and unemployment.
Worksheets and Projects in Statistics for Economists
This is an open online course, available freely to independent learners but with a fee for students who want feedback from an instructor. The course makes much use of online text, diagrams and interactive assignments. It is comprised of four units: Exploratory Data Analysis, Producing Data, Probability and Inference. These are subdivided into a total of twelve modules and more than two hundred "pages" of material. It is similar to the companion course on Statistical Reasoning, but with a more classical treatment of probability.
School of Data is an extensive site aiming "to empower civil society organizations, journalists and citizens with the skills they need to use data effectively." The site includes many textual "courses" explaining topics such as Exploring and Understanding Data, Common Misconceptions, Data Cleaning, or Data Journalism. There are also "recipes" explaining how to do tasks with specific tools. Often the tools are simple and freely available, such as Google Spreadsheets. The content is freely reusable and makes copious use of graphs and illustrations.
This course webpage supports an introductory module on quantitative economics as taught by Fowad Murtaza and Domenico Tabasso at the University of Essex in 2009/10. It introduces students to the methods of quantitative economics, i.e. to how data are used in economics. Beginning from an elementary level (assuming no background in statistics), the course shows how economic data can be described and analysed. The elements of probability and random variables are introduced in the context of economic applications. The probability theory enables an introduction to elementary statistical inference: parameter estimation, confidence intervals and hypothesis tests. With these foundations, students are then introduced to the linear regression model that forms a starting point for econometrics. It includes a course outline / handbook, lecture presentations, lecture notes, coursework assignments, problem sets with solutions and statistical data.