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Introduction to Statistics: Probability - University of California



Informazione importanti

  • Corso
  • Online
  • Quando:

An introduction to probability, with the aim of developing probabilistic intuition as well as techniques needed to analyze simple random samples.With this course you earn while you learn, you gain recognized qualifications, job specific skills and knowledge and this helps you stand out in the job market.

Informazione importanti

Requisiti: High school arithmetic, good comprehension of English, knowledge of the material of Stat2.1x, with emphasis on histograms, averages, SDs, and the normal curve.


Dove e quando

Inizio Luogo

Cosa impari in questo corso?

Probability theory


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Statistics 2 at Berkeley is an introductory class taken by about 1000 students each year. Stat2.2x is the second of three five-week courses that make up Stat2x, the online equivalent of Berkeley's Stat 2.

The focus of Stat2.2x is on probability theory: exactly what is a random sample, and how does randomness work? If you buy 10 lottery tickets instead of 1, does your chance of winning go up by a factor of 10? What is the law of averages? How can polls make accurate predictions based on data from small fractions of the population? What should you expect to happen "just by chance"? These are some of the questions we will address in the course.

We will start with exact calculations of chances when the experiments are small enough that exact calculations are feasible and interesting. Then we will step back from all the details and try to identify features of large random samples that will help us approximate probabilities that are hard to compute exactly. We will study sums and averages of large random samples, discuss the factors that affect their accuracy, and use the normal approximation for their probability distributions.

Be warned: by the end of Stat2.2x you will not want to gamble. Ever. (Unless you're really good at counting cards, in which case you could try blackjack, but perhaps after taking all these edX courses you'll find other ways of earning money.)

The fundamental approach of the series was provided in the description of Stat2.1x and appears here again: There will be no mindless memorization of formulas and methods. Throughout the course, the emphasis will be on understanding the reasoning behind the calculations, the assumptions under which they are valid, and the correct interpretation of results.

What you'll learn

  • What is a random sample, and how does randomness work
  • How to work with exact calculations of chances when the experiments are small
  • How to identify features of large random samples that will help us approximate probabilities that are hard to compute exactly

Ulteriori informazioni

Ani Adhikari Ani Adhikari, Senior Lecturer in Statistics at UC Berkeley, has received the Distinguished Teaching Award at Berkeley and the Dean's Award for Distinguished Teaching at Stanford University. While her research interests are centered on applications of statistics in the natural sciences, her primary focus has always been on teaching and mentoring students. She teaches courses at all levels and has a particular affinity for teaching statistics to students who have little mathematical preparation. She received her undergraduate degree from the Indian Statistical Institute, and her Ph.D. in Statistics from Berkeley. Philip B. Stark Philip B. Stark is Professor of Statistics at University of California, Berkeley where he developed the university's first online course.