Sampling Biological Populations
Basic Principles
Sampling 101
An Overview of Today’s Class
• What is sampling and why does it matter?
What
Why
Examples
• Qualitative vs Quantitative Sampling
Key points to get out of today’s lecture: What is sampling,
why sample, and why does it matter how you do it.
Readings: Ch. 7:76-81; Ch 8:102-127, 134-148; White et al.
Start Now!!
Steps in Conducting an Assessment using
Inventory and Monitoring
What is “sampling” ?
1. Develop Problem Statement—may include goals
Elzinga et al’s (p. 76) definition:
2. Develop Specific Objectives
3. Determine important data to collect
4. Determine how to collect and analyze data
“Sampling is the act or process of selecting a part of something
with the intent of showing the quality, style,
or nature of the whole.”
A more precise definition:
The act of selecting units for measurement
from a clearly defined population
5. Collect data
6. Analyze data
7. Assess data in context of objectives
Example of Populations
Biological Population
What is a population in relation to sampling?
Biological population
Statistical population
Why sample?
Complete enumeration or the study of all possible cases of interest
is usually impossible. In these typical cases, sampling methods are
used.
Sampling allows one to learn some aspect of the entire
population when enumerating the entire population
is not possible or desirable.
Sampled Population
Other reasons for sampling?
• reduce costs (time and effort) associated with
characterizing a population
Target Population
• may improve accuracy by allowing more time to be spent on
A smaller fraction of the population
Statistical Population
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Why sample?
Did you sample or “census” during your summer projects?
Examples of objectives where sampling is not needed?
Why sample? A precise understanding
“Good” sampling procedures allow you to make inductive inferences
on the population of interest. Inappropriate sampling simply does
not (=invalid inference).
Inductive inference: The generalization from a particular set
of data to the class of all similar data The conclusions from the
set of data is intended to go beyond the particular study.
“…process of generalizing to the population from the sample..”
Elzinga –p. 76
Examples of objectives where sampling is needed?
Without proper sampling, only conclusions about the sample
can be made; in some cases, that is all that is needed.
In most cases, this is insufficient.
Your Example of Sampling Biological Populations?
The Relation between Sampling and Statistics
Can you make perfect generalizations
from a sample to the population?
There is uncertainty in inductive inference.
The field of statistics provides techniques for
making inductive inference AND for providing means of
assessing uncertainty.
Bias vs Precision
Statistics:
“…an area of science concerned with development
of a practical theory of information. It involves sampling,
design of experiments, analysis of information, estimation
of parameters and testing of hypotheses. It is the basis for
inductive inference….”
From White et al. 1982
Bias (accuracy): Essentially, the “closeness” of a measured
value to its true value; the average performance
of an estimator
Precision:
The “closeness” of repeated measurements
of the same quantity; the repeatability of a
result.
Read chapter in White et al.
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Consider Test Question:
Selecting Random Samples
Qualitative Sampling Techniques
vs
Quantitative Sampling
Key points to get out of today’s lecture:
What is sampling
Pdf
Why sample
Why does it matter how you do it
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