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Every bonus point earned helps your overall grade, but even if you do no bonus work, you can still get 100% for the course. In other words, bonus points can only help you. Bonus points are extra credit.
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.
The Stat 100 Team has a group of highly trained students 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.
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.
Course Outline. Study Design: observational studies vs. randomized experiments, why randomized controls are key, confounders in observational studies, Simpson’s Paradox, intent to treat analysis, etc. Descriptive Statistics: mean, median, SD, histograms, box plots, normal curve, etc.
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.
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.
