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  1. STAT 100 Office Hours will be offered each week Monday, Tuesday, Wednesday, Thursday, Friday from 2pm-5pm in the Computer Applications Building (CAB). The room number is 171 and CAB is on 6th and Springfield. Office hours start Week 2 :) We also have online office hours Monday and Wednesday evenings from 8-10pm on zoom!

  2. karleflanagan.github.io › stat100S20 › pagesSTAT 100 - GitHub Pages

    STAT 100 Syllabus Spring 2020 (View PDF) Instructor Contact Information. L2 (In-Person) & KF (Online) Instructor: Karle Flanagan. Email: stat100flanagan@gmail.com. L1 (In-Person) Instructor: Kelly Findley. Email: kfindley@illinois.edu. Course Webpage. https://go.illinois.edu/stat100. You can also google “stat 100” :) Course Materials.

  3. stat100website.web.illinois.eduSTAT 100

    In Stat 100, we use statistics to research a topic we're all interested in - ourselves. We collect data on ourselves through anonymous surveys, largely on the sort of social questions on which students have shown intense interest.

  4. The Stat 100 Team has a group of highly trained graders who know every trick in the book for catching cheaters. We hand grade each of the exams and have multiple versions of all exams. They may look identical at first glance, but they are not.

  5. stat100netmath.web.illinois.edu › syllabusStat 100 NetMath Syllabus

    1. Public Stat100 Netmath website. Exam Study Guides, Data Program, p-value calculator and General Course Information are posted on the Public Course Website. https://stat100netmath.web.illinois.edu. 2. LON-CAPA site. All homework, surveys and bonus work are submitted and graded immediately on Lon Capa.

  6. STAT 100 Statistics credit: 3 Hours. First course in probability and statistics at a precalculus level; emphasizes basic concepts, including descriptive statistics, elementary probability, estimation, and hypothesis testing in both nonparametric and normal models.

  7. This class covers the same statistical content as Stat 100, but you learn Python programming and get experience analyzing real data. We are dedicated to helping students on the U of I campus learn and understand basic statistical concepts so they can understand and make sense of things that are interesting or important to them.