Not specifically aimed at economists, but this is an overview of errors and fallacies in the use of statistics for scientific inference. It presumes no prior knowledge of statistics. Base rate fallacies, underpowered tests, misinterpretation of significance, and regression to the mean are among the topics.
Online Text and Notes in Statistics for Economists
This is a general introduction to statistics in the form of an interactive online textbook, available for adaptation and reuse under an attribution-only licence. The site describes the book as "designed for the one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it." The whole book or individual pages can be downloaded in e-book formats. OpenStax is a project hosted at Rice University and supported by a group of educational charities.
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.
A 14-chapter, free online textbook in general introductory statistics that has been built up by wiki-style contributions from named contributors. Each chapter has multiple sections, each with key points, definitions, text, images, and quizzes. Some customisation and adaptation is allowed by the site's free licence. Paying a fee (per student per class) unlocks other customisation features such as VLE integration.
These case studies in data search, management and economic interpretation are aimed at first-time students of economics. They are downloadable in Word format with embedded links, to adapt, print and/or put in a virtual learning environment. They were produced by Dean Garratt and Stephen Heasell, Nottingham Trent University as part of an Economics Network project. They cover topics such as economic growth, house prices, household debt, consumption spending and government spending.
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.
Detailed lecture notes in PDF, reading list, past exams, and assignments from a 2009 course based on Larsen and Marx. Introduction to Mathematical Statistics and Its Applications. Available in Turkish as well as English.
Part of the MIT OpenCourseWare website, this page provides access to all the materials for Introduction to Statistical Method in Economics, as taught by Herman Bennett in spring 2006. The site includes a course syllabus, details of readings, lecture notes, assignments, exams and links to related Internet resources. Users can access the course online or download the whole thing as a .zip file.
Lecture notes and assessment materials from a general undergraduate course in statistical thinking taught in 2011 and based on the Tamhane & Dunlop textbook Statistics and Data Analysis: From Elementary to Intermediate. Topics include "Summarizing and Exploring Data", "Basic Concepts of Inference", "Inferences for Proportions and Count Data", "Similar Linear Regression and Correlation", and"Multiple Linear Regression"
This is an open online course, available freely to independent learners but with a fee for students. 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.
These free course materials require a login, either via Google, Facebook or a Udacity account. They cover "Visualizing relationships in data", "Probability", "Estimation", "Outliers and Normal Distribution", "Inference", and "Regression". The "classroom" link takes you to a large number of short YouTube videos each explaining a different step. The "Materials" link takes you to detailed, line by line transcripts which can be downloaded as PDFs. These include some formative questions. As with other MOOCs, there is a forum for learners to discuss questions arising from the material.
These free course materials require a login, either via Google, Facebook or a Udacity account. The course is organised in six modules and aims to cover the basics of statistical research using everyday examples. The "Materials" button links to downloadable videos, an index of concepts and a booklet of notes. "Classroom" leads to a series of short videos with interactive features. As with other MOOCs, there is a forum where learners can discuss questions.
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.
Seeing Statistics is an online text book teaching statistics using the Internet. It requires registration before full use, but a sample tour is available for free. Text includes glossary and calculator. The site uses a succession of pop-up boxes for navigation which may be confusing to users or not appear if pop-ups are disabled by your Internet browser.
This is a free online textbook on probability and statistics, making a lot of use of algebra. It starts with revision of mathematical tools including differentiation, has sections on foundations of probability and moves to more advanced topics such as Markov's inequality, probability mass and density, asymptotic theory and mathematical foundations of statistics. The site comes with a glossary.
The Chance project aims to help teachers and lecturers teach a basic understanding of probability and statistics. This page hosts examples of probabilistic and statistical reasoning, with links to related activities, simulations, videos, and data sets. Related links are also included.
Sixty types of data visualisation are given short explanations here, including density plots, population pyramids, chloropleth maps and Sankey diagrams. The site discusses some advantages and disadvantages of each. Each entry has a very short video clip.
The StatSoft: electronic statistics textbook is an online text introducing statistical concepts. It "begins with an overview of the relevant elementary (pivotal) concepts and continues with a more in depth exploration of specific areas of statistics." A glossary of statistical terms and a list of references for further study are included.
This course page supports an MBA course at the University of Portland, as taught by Todd Easton in 2008. It covers Statistical and Quantitative Analysis and presents tools for descriptive statistics and details their effective use. The page features a range of course materials - syllabus, past exams, Java applets etc. but perhaps most importantly it includes a booklet on Excel skills, with accompanying data.
SurfStat Australia is an online text in introductory Statistics produced at the University of Newcastle in Australia. It has five main sections: "Summarising and Presenting Data," "Producing Data," "Variation and Probability," "Statistical Inference" and "Control Charts". Text and images are interspersed with simple interactive quizzes.
HyperStat online is an introductory statistics textbook by David Lane of Rice University. It is arranged into 18 chapters, uses many interactive demonstrations and the textual content is broken into small chunks on successive pages. Each chapter ends with exercises, and offers selected answers. It also includes links to related material, recommended books and more information on how to use HyperStat in teaching.