Integrating Statistical Software
Into a Fisheries Course
Joshua K. Raabe
Teaching Partners – Pedagogy Project
WATR 353/553 – Fish Population Dynamics
•  Use math & statistics to analyze fisheries data
•  Inform management, research questions, make predictions
•  Common analyses
•  T-test, ANOVA, linear regression
•  Fisheries specific analyses
•  Non-linear regression
Microsoft Excel
+ Previously used in this course, capable of most analyses
+ Students familiar, widely available, “user” friendly
+ Students “see” steps in the analyses
–  Not overly powerful / made for complex analyses
–  Slower process
–  Mistakes common
FAMS: Fisheries Analysis & Modeling Simulator
+ User friendly, made for fisheries applications
+ Fast, accurate process
+ Great for entering & organizing data
–  $150 for an individual license
–  “Black box” – students do not see steps in analyses
–  Only does certain analyses
Program R
+ Free
+ Very powerful, fast process (after initial efforts)
+ Capable of all analyses, some fisheries packages available
–  Not user friendly, requires coding, steep learning curve
–  Errors can occur when coding
–  Increasing use by researchers, but fewer biologists
Fall Semester
•  Microsoft Excel used in all labs
•  Step-by-step instructions, reduced as semester went on
•  FAMS used in two labs
•  One to confirm results, one to do more complicated analysis
•  Step-by-step instructions
•  Program R used in two different labs
•  One to confirm results, one to do more complicated analysis
•  Provided code, step-by-step instructions
Microsoft Excel
•  Skill levels increased
•  Reduce instructions
Percent Responents
•  Preferred for common
analyses
60
Before
After
50
40
30
20
10
0
0
•  Numerous errors
occurred, some caught
during lab, others not
1
2
3
Self-Identified Skill Level
4
FAMS: Fisheries Analysis & Modeling Simulator
•  Preferred for complex
analyses
•  Few errors occurred
Percent Responents
•  Skill levels increased
100
90
80
70
60
50
40
30
20
10
0
Before
0
After
1
2
3
Self-Identified Skill Level
4
Program R
•  Preferred by a few
•  Use more, or not at all
•  Few errors occurred, but
code provided
Percent Responents
•  Skill levels increased
100
90
80
70
60
50
40
30
20
10
0
Before
0
After
1
2
3
Self-Identified Skill Level
4
Moving Forward
•  Microsoft Excel: continue using
•  FAMS: more labs to confirm Excel results
•  Program R: continue “introduction”, incorporate into
senior level course or separate course