Courses for Graduate Students

Introductory Statistics Courses

*This list is current as of January 2013. Please check UBC’s course calendar for changes.

  • LFS 252 Land, Food, and Community: Quantitative Data Analysis: Introduction to tools needed for data analysis of the economic, ecological, health, and scientific components of land and food systems. Second term only.
  • FRST 231 Introduction to Biometrics: Basic theories of probability and statistics. Sampling distribution, methods of estimation and hypothesis testing; goodness of fit and tests for independence; analysis of variance, regression and correlation. First and second term. Also online.
  • FRST 430 Advanced Biometrics: Analysis of variance, multiple regression and analysis of covariance. Design and analysis of experiments. First term only.
  • FRST 531 Multivariate Statistical Methods: Multivariate analysis of variance, cluster, principal components, factor, canonical and discriminant analysis. Theory and conceptual background are presented but emphasis is on selection of appropriate analysis and interpretation of results. Examples from forestry and related fields are analysed by computer programs at UBC. Second Term only.
  • FRE 385 Quantitative Methods for Business and Resource Management: Applied problem solving using spreadsheet and database software. Cases concern statistical analysis, data manipulation, financial statements, linear programming and simulation. Second term only.
  • ECON 325 Introduction to Empirical Economics: Essentials of probability and statistics for applied work in economics. Topics include descriptive statistics, probability, estimation, hypothesis testing, and analysis of variance. Credit will be granted for only one of ECON 325 or STAT 200. First term only.
  • BIOL 300 Fundamentals of Biostatistics: Statistical procedures for biological research; estimation, hypothesis testing, goodness of fit, analysis of variance and regression; use of computers for statistical analysis. Syllabus: First and second term.
  • 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. First term only.