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Alex Shum

Data Scientist at Apple.

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Teaching and TA assignments.

Iowa State University


STAT 101. Principles of Statistics. (Fall 2014: , Spring 2014: Evaluations

Statistical concepts in modern society; descriptive statistics and graphical displays of data; the normal distribution; data collection (sampling and designing experiments); elementary probability; elements of statistical inference; estimation and hypothesis testing; linear regression and correlation; contingency tables.


STAT 104. Introduction to Statistics. (Fall 2012, Spring 2013)
Statistical concepts and their use in science; collecting, organizing and drawing conclusions from data; elementary probability; binomial and normal distributions; regression; estimation and hypothesis testing. For students in the agricultural and biological sciences.

STAT 226. Introduction to Business Statistics I. (Fall 2013)
Obtaining, presenting, and organizing statistical data; measures of location and dispersion; the Normal distribution; sampling and sampling distributions; elements of statistical inference; estimation and confidence intervals; hypothesis testing; inference for simple linear regression analysis; use of computers to visualize and analyze data.

STAT 330. Probability and Statistics for Computer Science. (Fall 2012)
Topics from probability and statistics applicable to computer science. Basic probability; Random variables and their distributions; Stochastic processes including Markov chains; Queuing models; Basic statistical inference; Introduction to regression.

STAT 401. Statistical Methods for Research Workers. (Spring 2013, Summer 2012)
Graduate students without an equivalent course should contact the department. Methods of analyzing and interpreting experimental and survey data. Statistical concepts and models; estimation; hypothesis tests with continuous and discrete data; simple and multiple linear regression and correlation; introduction to analysis of variance and blocking.

University of Hawaii


MATH 307 Linear Algebra and Differential Equations.
Introduction to linear algebra, application of eigenvalue techniques to the solution of differential equations.