STAT 360
Statistical Inference
Spring 2022
Division III
Quantitative/Formal Reasoning
This is not the current course catalog
Class Details
How do we estimate unknown parameters and express the uncertainty we have in our estimate? Is there an estimator that works best? Many topics from introductory statistics such as random variables, the central limit theorem, point and interval estimation and hypotheses testing will be revisited and put on a more rigorous mathematical footing. The focus is on maximum likelihood estimators and their properties. Bayesian and computer intensive resampling techniques (e.g., the bootstrap) will also be considered.
The Class:
Format: lecture; For the Spring 2021 semester, synchronous zoom lectures are planned, where the instructor uses Google's jamboard to interact with students
Limit: 15
Expected: 15
Class#: 3293
Grading: no pass/fail option, yes fifth course option
Limit: 15
Expected: 15
Class#: 3293
Grading: no pass/fail option, yes fifth course option
Requirements/Evaluation:
Homework, Quizzes, Exams
Prerequisites:
MATH 250, STAT 201 or 202, STAT 341
Enrollment Preferences:
Statistics majors
Distributions:
Division III
Quantitative/Formal Reasoning
QFR Notes:
A rigourous mathematical course laying the foundation for reasoning with data
Class Grid
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HEADERS
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CLASSESColumn header 2DREQColumn header 3INSTRUCTORSColumn header 4TIMESColumn header 5CLASS#
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STAT 360 - 01 (S) LEC Statistical Inference
STAT 360 - 01 (S) LEC Statistical InferenceDivision III Quantitative/Formal ReasoningTR 8:30 am - 9:45 am
Wachenheim 0173293
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