Applied Statistics 2B

Victoria University of Wellington

Course Description

  • Course Name

    Applied Statistics 2B

  • Host University

    Victoria University of Wellington

  • Location

    Wellington, New Zealand

  • Area of Study

    Mathematics, Statistics

  • Language Level

    Taught In English

  • Prerequisites

    STAT 292

  • Course Level Recommendations

    Upper

    ISA offers course level recommendations in an effort to facilitate the determination of course levels by credential evaluators.We advice each institution to have their own credentials evaluator make the final decision regrading course levels.

    Hours & Credits

  • Credit Points

    15
  • Recommended U.S. Semester Credits
    3 - 4
  • Recommended U.S. Quarter Units
    4 - 6
  • Overview

    This course gives a more advanced presentation of statistical methods appropriate for applications in the biological and social sciences. Illustrative examples throughout the course make use of the statistical software environment R. Topics include: ANOVAs, randomised blocks, nested designs, multiple linear regression, data exploration, introduction to likelihoods, use of AIC for model comparisons in exploratory studies, generalised linear models, logit link models for binary response variables, three-way contingency tables, log-linear models and an introduction to survival analysis.

    Course content
    This course is an extension of material covered in STAT 292. Further topics in ANOVA and regression are presented with examples in the biological, health and social sciences. Topics covered include: theory of one-way ANOVAs, permutation tests, randomised block designs, nested designs, linear regression, use of AIC for model comparisons in exploratory studies and introduction to generalised linear models.


    Course learning objectives
    Students who pass this course should be able to:

    • Understand and apply the basic theory and concepts of analysis of variance, permutation testing and multiple linear and Poisson regression.
    • Use the software program R to analyse data using ANOVA or permutation testing for one-way, randomised block or nested designs.
    • Use the software program R to perform multiple linear or Poisson regression, the associated diagnostics and variable selection techniques.
    • Interpret results of the above stated analyses.

Course Disclaimer

Courses and course hours of instruction are subject to change.

Eligibility for courses may be subject to a placement exam and/or pre-requisites.

Some courses may require additional fees.

Credits earned vary according to the policies of the students' home institutions. According to ISA policy and possible visa requirements, students must maintain full-time enrollment status, as determined by their home institutions, for the duration of the program.

Please reference fall and spring course lists as not all courses are taught during both semesters.

Availability of courses is based on enrollment numbers. All students should seek pre-approval for alternate courses in the event of last minute class cancellations

Please note that some courses with locals have recommended prerequisite courses. It is the student's responsibility to consult any recommended prerequisites prior to enrolling in their course.