Stats Refresher for Biologists in “R” software

• Start Date: May 09, 2017
• End Date: May 11, 2017
• Time: 8:30am-4:00pm
• City: Castlegar BC
• Venue: Selkirk College, Main campus Castlegar, Rm G17
• Instructor: Dr. Carl Schwarz

Course Description

Many scientific studies are full of statistical jargon, tables of averages and other statistics, and results of statistical tests which purport to prove a certain hypothesis. The purpose of this course was to review some of the basic sampling and experiment designs used by ecologists and to understand exactly what can and cannot be extracted from a set of data. With the advent of modern statistical packages, the analysis of data is fairly easy, but it is far too easy to get nonsense results. This course also reviewed common pitfalls in the analysis of data.

Prerequisites: A “basic” knowledge of statistics, i.e., usually a single course somewhere in your background.  A working knowledge of “R” software. If you are new to “R” then we have a 1/2 day Intro to “R” Software course taking place the day before this course! See here for more details.

Course content

1. Review of statistical concepts on estimates, standard errors, confidence intervals, p-values, bias, precision, accuracy, missing values, etc.

2. Overview of environmental monitoring designs

3. Overview of some basic sampling strategies

– simple random sample
– stratified sampling
– cluster sampling
– two stage sampling
– ratio estimation

4. Details on simple random sampling, stratified sampling, cluster sampling

– how to plan
– sample size requirements, etc.
– how to analyze
– pitfalls and which to use when

5. Overview of experimental designs (single factor, two factor)

6. Details on single factor designs

– two-sample t-test
– one way ANOVA
– multiple comparisons
– subsampling
– pseudo-replication
– pairing, blocking, etc.

7. Overview and details on single variable regression analysis

8. Overview and details of categorical data analysis

Instructor

Schwarz Dr. Carl Schwarz, Department of Statistics and Actuarial Science, Simon Fraser University. Carl has taught  many courses with CMI, and is back by popular request!  Learn more about Carl here, and feel free to contact him with your questions at cschwarz@stat.sfu.ca

Thanks to our partner and host: