SEI Materials Archive: Statistics

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A place to share course materials including videos, photos, tutorials, syllabi and other tools to assist with teaching and learning across all areas of undergraduate statistics.

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CU-IPHY 2800: Introduction to statistics

Introductory undergraduate statistics course (research methods, probability, sampling, descriptive and inferential statistics, hypothesis testing, correlation)

CU-IPHY 5800: Advanced Statistics and Research Methods in Integrative Physiology

Graduate course in biostatistics

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UBC-STAT 200: Elementary Statistics for Applications

Classical, nonparametric, and robust inferences about means, variances, and analysis of variance, using computers. Emphasis on problem formulation, assumptions, and interpretation.

UBC-STAT 203: Statistical Methods

Organizing, displaying and summarizing data. Inference estimation and testing for elementary probability models.

UBC-STAT 241: Introductory Probability and Statistics

Probability models, random variables and vectors, estimation, testing, regression, analysis of variance, goodness of fit, quality control.

UBC-STAT 251: Elementary Statistics

Probability, discrete and continuous random variables, joint probability distributions, estimation, hypothesis testing, regression, analysis of variance, goodness of fit.

UBC-STAT 300: Intermediate Statistics for Applications

Further topics in statistical inference, including parametric and non-parametric methods, goodness-of-fit methods, analysis of variance and covariance, regression analysis, categorical data analysis, experimental designs, time series, model fitting, and statistical computing.

UBC-STAT 302: Introduction to Probability

Basic notions of probability, random variables, expectation and conditional expectation, limit theorems. Equivalency: UBC MATH 302

UBC-STAT 305: Introduction to Statistical Inference

Review of probability theory. Sampling distribution theory, large sample theory and methods of estimation and hypothesis testing, including maximum likelihood estimation, likelihood ratio testing and confidence interval construction.

UBC-STAT 306: Finding Relationships in Data

Modeling a response (output) variable as a function of several explanatory (input) variables: multiple regression for a continuous response, logistic regression for a binary response, and log-linear models for count data. Finding low-dimensional structure: principal components analysis. Cluster analysis.

UBC-STAT 307: Statistics Laboratory I

Implementing theory in applications. Problem based learning. Generation and analysis of case data. Modelling, computation and reporting.

UBC-STAT 308: Statistics Laboratory II

Implementing theory in applications. Problem based learning. Generation and analysis of case data. Modelling, computation and reporting.

UBC-STAT 321: Stochastic Signals and Systems

Stochastic behaviour of signals and systems (e.g., communication systems); discrete and continuous probability; random processes; modeling and identification of linear time-invariant systems; binary hypothesis testing and decision making.

UBC-STAT 335: Statistics in Quality Assurance

Philosophy of quality improvement and total quality control. Definitions of quality. Deming's principles, Ishikawa's tools, control charts, acceptance sampling, continuous improvement, quality design.

UBC-STAT 344: Sample Surveys

Planning and practice of sample surveys. Random sampling, bias and variance, unequal probability sampling, systematic, multistage and stratified sampling, ratio and regression estimators, post-stratification, establishing a frame, pretesting, pilot studies, nonresponse and additional topics.

UBC-STAT 404: Design and Analysis of Experiments

Theory and application of analysis of variance for standard experimental designs, including blocked, nested, factorial and split plot designs. Fixed and random effects, multiple comparisons, analysis of covariance.

UBC-STAT 406: Methods for Statistical Learning

Flexible, data-adaptive methods for regression and classification models; regression smoothers; penalty methods; assessing accuracy of prediction; model selection; robustness; classification and regression trees; nearest-neighbour methods; neural networks; model averaging and ensembles; computational time and visualization for large data sets.

UBC-STAT 443: Time Series and Forecasting

Trend and seasonality, autocorrelation, stationarity, stochastic models, exponential smoothing, Holt-Winters methods, Box-Jenkins approach, frequency domain analysis.

UBC-STAT 445: Introduction to Exploratory Data Analysis

Methods for exploring and presenting the structure of data: one group of numbers, several groups, bivariate data, time series data and two-way tables. Data displays, outlier identification, transformations, resistant regression, several types of data smoothing, comparisons with standard statistical methods.