BIOL 4090 / 6090



Last Updated December 1, 2017

Please report any problems here:

khyrenbach (at) hpu (dot) edu



(last updated: Nov. 15)


Dr. David Hyrenbach


Oceanic Institute

Office Hours:

Tu & Th; 10:45 - 12:00 (HLC, AC 249)

M & F; 11:15 - 12:00 (HLC, AC 249)

or by appointment at CTSA #1, OI



We will use two texts:

Discovering Statistics Using R, 2012, Andy Field, Jeremy Miles and Zoe Field. Sage Publications, Thousand Oaks (USA)


ISBN: 9781446200469


A Primer of Ecological Statistics, 2004, Nicholas Gotelli and Aaron Ellison, Sinauer Associates Inc., Sunderland

ISBN: 0878932690

(On Reserve, Atherton Library)


Course Readings

The PDFs posted on this page are for class use only.

Please do not distribute.



Week 1 - Course Introduction and Foundations

Task for this Week: Review The Scientific Method


Lecture 1: Tuesday Aug. 29


Introduction - Three Statistical Frameworks



Lecture 2: Thursday Aug. 31



The Scientific Method & Hypothesis Testing



Assigned Reading:

Platt J.R. (1964)

Strong inference. Science, 146: 347-353

Assigned Reading:

Quinn J.F., & Dunham A.E. (1983)

On hypothesis testing in ecology and evolution. The American Naturalist, 122(5): 602-617


(PDF, 2 Mb)

Extra Reading:

O'Donohue, W., & Buchanan, J.A. (2001)

The weaknesses of strong inference. Behavior & Philosophy, 29: 1-20



Week 2 - Simple and Conditional Probability

Task for this Week: Review Simple and Conditional Probability



Lecture 3: Tuesday Sept. 5


Sampling and Probability



Assigned Reading:

Diamond, J. (1988).
Why cats have nine lives.
Nature 332 (6165): 586–587.

Extra Reading:

Lewison, R.L., Soykan, C.U., & Franklin J. (2009).
Mapping the bycatch seascape: multispecies and
multi-scale spatial patterns of fisheries bycatch.
Ecological Applications 19(4): 920–930.


(543 Kb)


Lecture 4: Thursday Sept. 7


Conditional Probability (and Bayesian Statistics)



Assigned Reading:

Silver, N. (2012). Less and less and less wrong. Pp. 232 - 261.

In: The Signal and the Noise. Penguin Press, New York.

Assigned Reading:

Marcus, G., & Davis, E. (2013) What Nate Silver Gets Wrong.

The New Yorker.


(32 Kb)

Extra Reading:

Is God Bayesian ? Unwim VS. Wiggins

(88 Kb)



Week 3 - Statistical Inference

Task for this Week: Making Statistical Predictions


Lecture 5: Tuesday Sept. 12


Extra Reading:

Fairfield-Walsh, C. Garrison, L. 2007. Estimated Bycatch of Marine Mammals and Turtles in the U.S. Atlantic Pelagic Longline Fleet During 2006. NOAA Technical Memorandum NOAA NMFS-SEFSC-560: 54 p.

(883 Kb)



Lecture 6: Thursday Sept. 14


QUIZ#1 (Sampling and Probability)



Assigned Reading:

Silver, N. (2012). How to drown in 3 feet of water. Pp. 176 - 203.

In: The Signal and the Noise. Penguin Press, New York.



Week 4 - R & Probability Distributions

Task for this Week: Working with Probability Distributions



Lecture 7: Tuesday Sept. 19


Statistical Inference and Reliability


(Review of Homework #2)


Lecture 8: Thursday Sept. 21


QUIZ#2 (Estimation: Central Tendency / Variability)


Estimation and Statistical Modelling


Assigned Reading:

Silver, N. (2012). Desperately Seeking Signal. Pp. 142 - 175.

In: The Signal and the Noise. Penguin Press, New York.




Week 5 - Parametric Assumptions

Task for this Week: Assumptions and Data Transformations


Lecture 9: Tuesday Sept. 26


Probability Distributions


Introduction to Graphical Exploration in R Comander


Assigned Reading:

Limbert, E., Stahel, W.A., & Abbt, M. (2001) Log-normal Distributions across the Sciences: Keys and Clues. Bioscience 51:5: 341-352.


(556 Kb)



Lecture 10: Thursday Sept. 28


QUIZ#3 (Z Scores and Confidence Intervals)


Statistical Assumptions


Week 6 - Assessing Normality

Task for this Week: Assessing Data Normality



Lecture 11: Tuesday Oct. 3


Data Transformations


RExam Dataset



Lecture 12: Thursday Oct. 5


QUIZ#4 (Assessing Normality: Assumptions & Approaches)


Dealing with the lack of Normality - Theory & Practice


Week 7 - Using Statistical Models to Test Hypotheses

Task for this Week: Start Exploring Statistical Models



Lecture 14: Thursday Oct. 12


QUIZ#5 (Assessing Normality - Descriptive Statistics)


Introduction to Correlation



Week 8 - Correlation and Regression

Task for this Week: Explore Correlation and Regression



Lecture 16: Thursday Oct. 19


Simple Linear Regression


AlbumSales1 Dataset



Week 9 - Comparing Two (or more) Means

Task for this Week: Consider Multiple Variables



Lecture 17: Tuesday Oct. 24


Multiple Linear Regression


AlbumSales2 Dataset



Lecture 18: Thursday Oct. 26


QUIZ#6 (Correlation and Linear Regression)


Comparing Two Means


SpiderLong Dataset SpiderWide Dataset


Week 10 - Comparing Two (or more) Means

Task for this Week: Explore ANOVA



Week 11 - Multi-way ANOVA

Task for this Week: Continue Exploring ANOVA




Lecture 21: Tuesday Nov. 7

Two-Way ANOVA (First Part)

QUIZ#7 (Comparing Two Means)


Lecture 22: Thursday Nov. 9


Multifactor ANOVA: Factorial and Nested Designs (Second Part)




Week 12 - Other Statistical Applications

Task for this Week: Explore Other Statistical Tests



Lecture 23: Tuesday Nov. 14








Lecture 24: Thursday Nov. 16


QUIZ#8 (Analysis of Variance)



Contingency Tests




CatsAndDogs Dataset


Week 13 - Other Applications

Task for this Week: Explore Other Statistical Concepts



Lecture 25: Tuesday Nov. 21



Nonparametric Tests



DrugDataset SoyaDataset




Thursday Nov. 23


NO CLASS - Thanksgivings



Week 14 - Wrap-Up

Task for this Week: Wrap Up



Lecture 26: Tuesday Nov. 28


QUIZ#9 (Contingency Tables and Nonparametric Tests)






Extra Reading:

Dayton, P.K. (1998) Reversal of the burden of proof in fisheries management. Science 279 (5352): 821-822.

(655 Kb)

Extra Reading:

Benjamin, D.J. et al. (2017) Redefine Statistical Significance. PsyArXiv, 22 July 2017. Web.

(7.1 Mb)

Extra Reading:

Unreliable Research. trouble at the lab. The Economist, October 19th, 2013

(217 Kb)





Lecture 27 : Thursday Nov. 30


Final Exam Review: Jeopardy


Week 15 - Finals' Week

Thursday Dec. 7


(9.10 - 11.35)


Submit Take-home Final


Take In-Class Final









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