Syllabus - Mathematics, Statistics and Computer Science

Marquette University
MSCS6010
Syllabus
Daniel B. Rowe, Ph.D.
Professor
Department of Mathematics,
Statistics, and Computer Science
Copyright 2014 by D.B. Rowe
1
Marquette University
MSCS6010
Department of Mathematics, Statistics, and
Computer Science
Marquette University
Syllabus
Fall 2014
Course: MSCS 6010 Probability
Time: TuTh 5:00-6:15 Cudahy Hall 126
Instructor: Daniel B. Rowe, Ph.D.
D.B. Rowe
2
Marquette University
MSCS6010
Office Hours: TuTh 4:00-5:00 pm
Office: Cudahy Hall 313
E-mail: [email protected]
Text: (reference) Casella, G. & Berger, R.L. (2002).
Statistical Inference, Second edition, Duxbury.
ISBN: 0-534-24312-6
Grading: A midterm (in class) on Oct 24, weekly homework &
class participation, and a final exam (possibly in class) on
Dec 9, 5:45 pm – 7:45 pm.
Homework & Participation (30%), Mid-Term (30%), Final (40%).
D.B. Rowe
3
Marquette University
MSCS6010
Matlab Introduction
-Arithmetic and Variables, Arrays and Indexing, Programming,
Plotting, Functions and m-files, Importing and Exporting Images
Math Review
-Differentiation, Integration
Probability Theory
-Sets, Events, Probability of events, Combinations and
Permutations, RVs, PMFs, PDFs, CDFs
D.B. Rowe
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Marquette University
MSCS6010
Discrete Distributions
-properties, moments, expectation, MGF, transformation of
variable
-Bernoulli, binomial, Poisson, hypergeometric
Continuous Distributions
-properties, expectation, moments, MGF, transformation of
variable
- uniform, beta, normal, chi square, gamma, exponential,
student t, F,
- random samples, likelihood, MLE, hypothesis testing, LRT
D.B. Rowe
5
Marquette University
MSCS6010
Multivariate Distributions
-normal, student t, Wishart, inverse Wishart
Bayesian Statistics
-prior, likelihood, posterior, posterior estimation
Numerical Flavor
All slides are a summary of the material and do not
contain all detail. Book is ultimate authority.
D.B. Rowe
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