Research & Statistics

Courses listed here will address research methodology, statistics for use in the social sciences, and laboratory procedures. Most will not require any previous mathematical courses beyond that which is covered in high school. The rating represents the breadth of material available, the effectiveness of the lecturer, and the accessibility of the website and lecture topics in general. If you have comments or suggestions, feel free to email me at eric@psychlectures.com. Enjoy!

Introduction to Statistics

Prof. Nicholas Gilpin, Spring 2009 – UCSD podcasts

[mp3 audio]

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Design and Analysis of Experiments

Prof. David Groppe, Spring 2009 – UCSD podcasts

[mp3 audio]

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Research and Data Analysis in Psychology

Fredric Theunissen, Fall 2008 – UC Berkeley Webcasts

“The course will concentrate on hypothesis formulation and testing, tests of significance, analysis of variance (one-way analysis), simple correlation, simple regression, and nonparametric statistics such as chi-square and Mann-Whitney U tests.

[mp3 audio]

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Introduction to Statistics

Fletcher Ibser, Fall 2008 – UC Berkeley Webcasts

“Population and variables. Standard measures of location, spread and association. Normal approximation. Regression. Probability and sampling. Binomial distribution. Interval estimation. Some standard significance tests.

[mp3 audio]

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Statistical Inferences for Social and Life Scientists

Fletcher Ibser, Fall 2008 – UC Berkeley Webcasts

[mp3 audio]

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Marathon Moral Reasoning Laboratory

Prof. Rebecca Saxe et al., January 2007 – MIT OpenCourseWare

“This seminar focuses on the cognitive science of moral reasoning. Philosophers debate how we decide which moral actions are permissible. Is it permissible to take one human life in order to save others? We have powerful and surprisingly rich and subtle intuitions to such questions.

In this class, you will learn how intuitions can be studied using formal analytical paradigms and behavioral experiments. Thursday evening, meet to learn about recent advances in theories of moral reasoning. Overnight, formulate a hypothesis about the structure of moral reasoning and design a questionnaire-based experiment to test this. Friday, present and select 1-2 proposals and collect data; we will then reconvene to analyze and discuss results and implications for the structure of the moral mind.”

[syllabus] – [required readings] – [assignments] – [downloadable content]

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Laboratory in Cognitive Science

Prof. Aude Oliva, Fall 2005 – MIT OpenCourseWare

“[This course] teaches principles of experimental methods in human perception and cognition, including design and statistical analysis. The course combines lectures and hands-on experimental exercises and requires an independent experimental project. Some experience in programming is desirable. To foster improved writing and presentation skills in conducting and critiquing research in cognitive science, students are required to provide reports and give oral presentations of three team experiments. A fourth individually conducted experiment includes a proposal with revision, and concluding written and oral reports.”

[syllabus] – [calendar] – [required readings] – [lecture notes] – [assignments] -[related resources] – [downloadable content]

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Statistical Methods in Brain and Cognitive Science

Dr. Ruth Rosenholtz, Spring 2004 – MIT OpenCourseWare

“This course emphasizes statistics as a powerful tool for studying complex issues in behavioral and biological sciences, and explores the limitations of statistics as a method of inquiry. The course covers descriptive statistics, probability and random variables, inferential statistics, and basic issues in experimental design. Techniques introduced include confidence intervals, t-tests, F-tests, regression, and analysis of variance. Assignments include a project in data analysis.”

[syllabus] – [calendar] – [required readings] – [lecture notes] – [assignments] -[study materials] – [downloadable content]

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Brain Laboratory

Prof. Earl Miller & Prof. Sonal Jhaveri, Spring 2002 – MIT OpenCourseWare

“Consists of a series of hands-on laboratories designed to give students experience with common techniques for conducting neuroscience research. Included are sessions on anatomical, ablation, neurophysiological, and computer modeling techniques, and ways these techniques are used to study brain function. Each session consists of a brief quiz on assigned readings that provide background to the lab, a lecture that expands on the readings, and that week’s laboratory. Lab reports required. Students receive training in the art of scientific writing and oral presentation with feedback designed to improve writing and speaking skills. Assignments include two smaller lab reports, one major lab report with revision, and an oral report.”

[syllabus] – [calendar] – [laboratory guides] – [assignments] -[study materials] – [downloadable content]

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