AndeeKaplan

Assistant Professor at Colorado State University Statistics

Courses Taught at Colorado State University

Stat 730 - Advanced Theory of Statistics I

Concepts in probability theory, e.g., independence, laws of large numbers, convergence in distribution, conditional expectation, and some key topics in statistical inference presented using the fundamentals from earlier in the course.

Spring 2019

Stat 630 - Advanced Statistical Data Analysis

Advanced statistical modeling techniques and data analysis methods, including likelihood-based methods, M-estimation, bootstrap and EM algorithm, and other advanced topics. For example, Jackknife, permutation tests, and nonparametric statistics.

Fall 2024 | Fall 2023


Staa 577 - Statistical Learning and Data Mining

Applications-oriented overview into how to use statistical methods to do data mining, inference, and prediction. A variety of statistical learning and data mining techniques are presented. These techniques include but are not limited to: linear regression, classification, resampling methods, model selection and regularization, splines and GAMs, tree-based methods, and SVMs.

Fall 2024 | Spring 2024 | Fall 2023 | Spring 2023

Dsci 445 - Statistical Learning

Algorithms and statistical methods for regression, classification, and clustering; hands-on experience in analyzing data and running machine learning experiments.

Fall 2024 | Fall 2023 | Fall 2022 | Fall 2021 | Fall 2020


Stat 400 - Statistical Computing

Computationally intensive statistical methods are a key component to modern data analysis methods. This course prepares students to use statistical software to implement both traditional and state-of-the-art methods in computational statistics and recognize situations where these methods are required.

Fall 2022 | Fall 2021 | Fall 2020 | Fall 2019

Courses Taught at Iowa State University

Stat 305 - Engineering Statistics

This class covers principles of engineering data collection, descriptive statistics, elementary probability distributions, principles of experimentation, confidence intervals and significance tests, one-, two-, and multi-sample studies, and regression analysis.

Summer 2017 | Spring 2017

Agron 590RD - Data Stewardship for Earth Systems Scientists

Teaches fundamental data skills required for successful, collaborative, and reproducible research within the context of plant, soil, and atmospheric sciences. This course focuses on the technology and theory behind data stewardship in the 21st century.

Fall 2016


Stat 226 - Introduction to Business Statistics I

Introductory statistics for undergraduate students in the College of Business. This course emphasizes the use of statistics in business situations and use of computers to visualize and analyze data.

Spring 2013

Courses TAed at Iowa State University

Stat 226 - Introduction to Business Statistics I

Introductory statistics for undergraduate students in the College of Business. This course emphasizes the use of statistics in business situations and use of computers to visualize and analyze data.

Fall 2012

Stat 326 - Introduction to Business Statistics II

Second statistics for undergraduate students in the College of Business. This course covers multiple regression analysis, regression diagnostics, model building, applications in analysis of variance and time series, random variables, distributions, conditional probability, statistical process control methods, use of computers to visualize and analyze data.

Fall 2014

Courses TAed at The University of Texas

M 302 - Introduction to Mathematics

Introductory mathematics intended primarily for general liberal arts students seeking knowledge of the nature of mathematics as well as training in mathematical thinking and problem solving.

Fall 2008

M 408D - Sequences, Series, and Multivariate Calculus

Introduction to the theory and applications of sequences and infinite series, including those involving functions of one variable, and to the theory and applications of differential and integral calculus of functions of several variables.

Spring 2009