Statistics One

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Description

When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

Statistics One is designed to be a friendly introduction to very simple, very basic, fundamental concepts in statistics.

About the Course

Statistics One is designed to be a friendly introduction to very simple, very basic, fundamental concepts in statistics. This course is, quite literally, for everyone. If you think you can't learn statistics, this course is for you. If you had a statistics course before but feel like you need a refresher, this course is for you. Statistics One also provides an introduction to the R programming language. All the examples and assignments will involve writing code in R and interpreting R output. R software is free! It is also an open source programming langu…

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Frequently asked questions

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When you enroll for courses through Coursera you get to choose for a paid plan or for a free plan

  • Free plan: No certicification and/or audit only. You will have access to all course materials except graded items.
  • Paid plan: Commit to earning a Certificate—it's a trusted, shareable way to showcase your new skills.

Statistics One is designed to be a friendly introduction to very simple, very basic, fundamental concepts in statistics.

About the Course

Statistics One is designed to be a friendly introduction to very simple, very basic, fundamental concepts in statistics. This course is, quite literally, for everyone. If you think you can't learn statistics, this course is for you. If you had a statistics course before but feel like you need a refresher, this course is for you. Statistics One also provides an introduction to the R programming language. All the examples and assignments will involve writing code in R and interpreting R output. R software is free! It is also an open source programming language. What this means is you can download R, take this course, and start programming in R after just a few lectures. Statistics may seem like a foreign language, and in many ways it is. The ultimate goal of Statistics One is to get people all over the world to speak this language. So consider this your first course in a new and exciting universal language!

About the Instructor(s)

Professor Andrew Conwayis a Senior Lecturer in the Department of Psychology at Princeton University. He has been teaching introduction to statistics for undergraduate students and advanced statistics for graduate students for 16 years. The first 8 years of his teaching career were at the University of Illinois in Chicago. He has been at Princeton since 2004. Professor Conway is originally from upstate New York and did his undergraduate work at Union College in Schenectady, NY where he majored in Psychology and Computer Science. For graduate school, Professor Conway attended the University of South Carolina where he earned a Masters degree and Ph.D. in Experimental Psychology with a minor in Statistics. Professor Conway also maintains an active research program and is the Principal Investigator of the Human Working Memory Lab in the Psychology Department at Princeton. He and his graduate students investigate the cognitive and neural mechanisms underlying memory, attention, and intelligence. This work has resulted in over 40 publications in various journals in Psychology and Neuroscience. He is also an Associate Editor for the Journal of Cognitive Psychology.

Course Syllabus

  • Week One: Random sampling and assignment. Distributions.
  • Week Two: Descriptive statistics. Measurement.
  • Week Three: Correlation. Causality.
  • Week Four: Multiple regression. Ordinary least squares.
  • Week Five: Confidence intervals. Statistical power.
  • Week Six: t-tests, chi-square tests. Analysis of Variance.

Recommended Background

Anyone and everyone is welcome to take this class.

Suggested Readings

Statistics, 4th Edition by Freedman, Pisani, & Purves. Norton Publishing (4th Edition)

Course Format

There will be three one-hour lectures per week. There will also be weekly quizzes and weekly "take-home" assignments. There will be a midterm exam and a final exam.

FAQ

  • What resources do I need for this class?

    All you need is an internet connection!

  • Does Princeton award credentials or reports regarding my work in this course?

    No certificates, statements of accomplishment, or other credentials will be awarded in connection with this course.

Provided by:

University: Princeton University

Instructor(s): Andrew Conway

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