Why Biologists Need Sampling, Experimental Design, and Statistics

1. Why Biologists Need Sampling, Experimental Design, and Statistics Based on Chapter 1 of D. Heath (1995). An Introduction to Experimental Design and Statistics for Biology. CRC Press.

2. What do biologists “do”? • Biologists study the living world through observation and experimentation • Two types of scientific questions: • Description (“WHAT?” questions) • Explanation (“HOW?” questions)

3. QUESTION: What is the mass of a M & M ?

4. In-Class Exercise • 1 person from each group will come up and choose 10 M &M from a jar • Each group will then use a balance to measure the mass of each of these 10 beans • Finally, each group will characterize the mass of the M & M in the jar

5. QUESTION: What is the mass of a M & M? • We could say the “true value” is: 1.63 g • Is it correct to say this? • NO, because there is always variation associated with our measurements!

6. VARIABILITY • Experimental variation: variability introduced by the observer/experimenter or by the techniques and equipment used • Organismal variation: natural variability in genotypes and phenotypes • Spatiotemporal variation: variability in the spatial and/or temporal distribution of organisms, ecosystems, etc. • PROBLEM: all of this variability gets in the way of (or should be a part of?) our attempts to describe and explain the living world!

7. How do we deal with variability? • One approach is to measure every single entity in every possible location of our population of interest (NOTE: this may not always be a “biological population”) • BUT, this is rarely possible in practice! • Potential solution: we measure a subset of all the possible entities (i.e., a sample) and use these values to make inferences about the population

8. Sampling and Experimental Design • We want our sample to be representative of all the possible observations in the population • Potential problems: • Bias: when certain observations occur more or less frequently in the sample than they do in the population • Sampling variation: chance variation in the makeup of a sample (aka, “sampling error”) • We can use the principles of experimental design to develop a sampling strategy that minimizes these problems

9. Sampling and Statistics We can assume that there is a “true value”, however: • Even with an effective sampling strategy, it will never be possible to obtain the “true” population value (due to sampling variation) • BUT, we can use statistical analysis to get a measure of how close our sample estimate is to the “true” value

10. Beyond Description: Explanation • Describing biological patterns is important, but we also want to understand the processes that generated the observed patterns • Explanation: involves identifying the factors or causes of what has been described • PROBLEM: the complexity and variability of biological systems often means there are many possible factors involved

11. EXAMPLE: Predator-Prey Relationships Predator density Prey density Environment

12. Observational Studies(aka, “Natural Experiments”) • After making hypotheses about potential factors, we can take advantage of naturally occurring variation in the factors to test for differences in the association among the variable of interest • Common in ecology • Problem: such studies cannot determine the direction of cause-and-effect (i.e., causal connections)

13. Manipulative Experiments • The investigator sets up the experiment so that the treatments differ only in the factor(s) of interest • Can be laboratory, greenhouse, or field experiments • Because we reduce possible confounding factors, we have much more confidence in the causal relationship between the factor(s) and the response variable

14. Experimental vs. Observational Studies • While manipulative experiments are the most effective method of establishing causal relationships, they have some drawbacks: • Focus on only a few factors • Experimental manipulation of factors may not be representative of “natural” conditions • Often limited to relatively small spatiotemporal scales • May not be feasible due to legal, ethical, and/or practical considerations

15. Summary • The starting point of all studies should be one or more well-defined research questions • Sampling, experimental design, and statistical analysis are crucial to almost all biological studies • It is essential to consider these three issues together and, ideally, before any of the practical work of the study is carried out

16. For next class: • Read Chapter 6 of Gotelli and Ellison (2004) • Read Hurlbert (1984 ) • Prepare a brief written summary (1 page) on an example of experimental design including: • Your research question and hypothesis • How you plan to eliminate alternative explanations and control for confounding factors as you evaluate your hypothesis • Homework 1 is due August 31: • Read Ehrlen 1992 and Harvell 1992 and answer the following questions • How these studies were pseudo-replicated? • How did this affect the information he presents?