Practical information for Biostats Course VHM 801 at AVC -
Fall Semester 2020
Course contents and aims
From the UPEI Calendar:
"This course provides the student with a working knowledge of the basic
statistical techniques used in veterinary science. Topics include
descriptive statistics, inferential statistics, non-parametric
statistics, analysis of variance, regression and correlation and
experimental design."
Keywords (mostly from the course announcement):
Data and Descriptive statistics,
Normal distribution,
Sampling and Design of studies (incl. experiments),
Probability and Random variables,
Binomial distribution,
Statistical inference: estimation, confidence intervals and tests,
Analysis of one and two continuous samples (t-tests),
Analysis of one and two discrete samples,
Two-way tables,
One-way analysis of variance (ANOVA),
Simple linear regression and correlation,
Introduction to multifactorial analysis (multiple regression, two-way ANOVA)
Nonparametric methods,
Introduction to sample size calculations,
Reporting of statistical analysis in papers.
Course content overview:
Basic concepts in statistical inference (estimation, confidence interval, test),
Models for and analysis of standard designs:
one and two samples, analysis of variance and regression,
Introductions to model validation, study and experimental design, sample size calculation and non-parametric methods.
Course aims:
- to provide an understanding of the basic principles/concepts of statistical
inference, to the level where the student is able to apply and interpret these,
both in familiar designs/models and more generally,
- to provide practical experience with the
statistical models covered in the course, to the level where the student
is able to apply the models and methods and to critically assess the results,
- to introduce advanced tools for model building (incl. experimental design)
and validation, to the level where the student is able to proceed to more
complex data structures (either by self study or in an advanced course).
Course prerequisites
- elementary mathematical calculus (familiarity with standard
functions, ability to solve and rearrange simple equations with
unknowns, use of a calculator),
- elementary computer applications (file management, spreadsheets
etc., but no prior knowledge of statistical package(s) required),
- no previous training in statistics required (nevertheless, it might
be helpful).
Course organization - adapted to online delivery
- Lectures - as asynchronous video lectures (approximately 2 hours weekly):
- explanation of concepts and presentation of new material,
including some computer demonstrations,
- review of simple, conceptual exercises,
- review of home assignments,
- Labs - as part synchronously streamed and part in-class only (2 hours weekly):
- computer demonstrations (streamed),
- class exercises, and individual work on exercises using calculator and computers,
- Lab reviews - as synchronously streamed sessions (2 hours weekly):
- reviews of selected lab problems,
- questions/discussion of lectures, textbook, exercises, home assignments etc.,
(small project)
- Homework:
- self study of textbook and course material in general,
- home assignments: 4 sets, of which the last may be replaced by analysis of own data
(small project),
- weekly on-line quizzes, to reinforce and support the learning,
- Examination:
- 60% home assignments,
- 20% online quizzes,
- 20% final take-home assignment.
Course material
- textbook: several options exist, see separate note,
- VHM 801 website: lecture overheads, solutions to
exercises and assignments, links, general information etc.,
- some additional lecture notes to parts of course not covered by
textbook,
- Moodle account for VHM 801 to
facilitate online communication, discussion etc.
Course software
The main statistical package for the course is Minitab (version 19). It is also
possible to use Stata (version 16, or 14-15), R software (version 3.0 or later) or any combination of these.
Henrik Stryhn
(hstryhn@upei.ca) 2020-09-02