Course Description

INTRO TO STATISTICS, STAT 100A

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A general introduction to descriptive and inferential statistics. Topics include histograms; descriptive statistics; probability; normal and binomial distributions; sampling distributions; hypothesis testing; and confidence intervals. Credit is awarded for one of the following STAT 100A or STAT 048.

Students MUST enroll in BOTH a discussion section AND a lab section for this course. After registration, Student Support will contact you to confirm your enrollment.

Key Information

Academic Calendar(opens in a new tab)

Credit: 5 quarter units / 3.33 semester units credit
UC Riverside, Statistics

Course Credit:

Upon successful completion, all online courses offered through cross-enrollment provide UC unit credit. Some courses are approved for GE, major preparation and/or, major credit or can be used as a substitute for a course at your campus.

If "unit credit" is listed by your campus, consult your department, academic adviser or Student Affairs division to inquire about the petition process for more than unit credit for the course.

UC Berkeley:
Unit Credit

UC Davis:
Course Equivalence: UCD STA 013
General Education: QL, SE.

UC Irvine:
Unit Credit

UC Los Angeles:
Unit Credit

UC Merced:
Unit Credit (see your Academic Advisor)

UC Riverside:
Major Requirement: requirement for minor in Statistics at UCR

UC San Diego:
General Education: TMC 1 course toward upper division disciplinary breadth if noncontiguous to major, Seventh - 1 course towards Alternatives - Quantitative Reasoning; ERC 1 course Formal Skills 
Major Preparation: For Cognitive Science Majors: taken together UCR STAT 100A & STAT 100B would count for UCSD COGS 14B - Introduction to Statistical Analysis

UC San Francisco:
Unit Credit

UC Santa Barbara:
Course Equivalence: Likely equivalent to PSTAT 5A or PSTAT 5LS after petition
General Education: This course will apply to Quantitative Relations automatically upon completion
Possible Area C after petition

UC Santa Cruz:
General Education: SR

Prerequisites

MATH 005 or MATH 006B or MATH 009A or MATH 09HA or MATH 007A; or consent of instructor.

Course Fees

OpenIntro Statistics 4th Edition: text (free online, ~$20 print copy) R and Rstudio: software (free) WebAssign: online homework (~$40)

More About The Course

Mandatory attendance for all class meetings (lecture, discussion and lab) weeks 0-2 is required for both enrolled and waitlisted students. Those who do not attend all enrolled sessions will be dropped from the class or from the waitlist.

Relevant Website

Course Creator

James Flegal
James Flegal is an Associate Professor of Statistics at the University of California, Riverside. He received his Ph.D. from the School of Statistics at the University of Minnesota. His research interests include statistical computing, Markov chain Monte Carlo, Bayesian statistical methods, and Monte Carlo standard errors. Prior to graduate school, James attended Northwestern University where he earned a B.S. in Mechanical Engineering. His professional career outside of academia includes modeling furnace systems with computational fluid dynamics algorithms and designing welded fabrications for a heavy equipment manufacturer. James Flegal is an Associate Professor of Statistics at the University of California, Riverside. He received his Ph.D. from the School of Statistics at the University of Minnesota. His research interests include statistical computing, Markov chain Monte Carlo, Bayesian statistical methods, and Monte Carlo standard errors. Prior to graduate school, James attended Northwestern University where ...

James Flegal is an Associate Professor of Statistics at the University of California, Riverside. He received his Ph.D. from the School of Statistics at the University of Minnesota. His research interests include statistical computing, Markov chain Monte Carlo, Bayesian statistical methods, and Monte Carlo standard errors. Prior to graduate school, James attended Northwestern University where he earned a B.S. in Mechanical Engineering. His professional career outside of academia includes modeling furnace systems with computational fluid dynamics algorithms and designing welded fabrications for a heavy equipment manufacturer.

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