INTRODUCTION

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ZOO 305

Animal Physiology

SECTION BA - Lab = 02:00-04:50 T
SECTION BB - Lab = 02:00-04:50 W
SECTION BC - Lab = 01:00-03:50 R
SECTION BD - Lab = 01:00-03:50 F

D. L. Claussen

OFFICE: 164 PSN

Office hrs: 12:00-01:00 T, 12:00-02:00 W

other hrs by appointment

Physiology is the study of FUNCTION.
The study of how animals (and their component parts) work

Claude Bernard (1813-1878) is recognized as the "father" of physiology.

The August Krogh Principle: "For many problems, there is an animal
on which it can be most conveniently studied"

SCIENCE is:
A way of knowing
A method of discovery

Science can be either "pure" or "applied",
but all science is based on OBSERVATION

Observation is a necessary component of science, but,
by itself, is not sufficient.

To be of any scientific value, observation must
be accompanied by reasoning.

Charles Darwin expressed this well when he stated,
"How odd it is that anyone should not see that all observation
must be for or against some view if it is to be of any service."

OBSERVATION

can be PASSIVE or ACTIVE

An active observation = an experiment

Claude Bernard nicely defined an experiment as "an induced or provoked observation"

TOOLS OF SCIENCE

These expand the limits of observation.
Mathematical tools are used to quantify observations
STATISTICS is used both to describe observational data and for decision making
HYPOTHESIS = "an educated guess"
The scientific method is largely based on developing and testing hypotheses.
We do not "prove" or "disprove" anything. Rather, we use statistics
to quantify the likelihood that a given hypothesis is correct.
We must be aware, however, that any conclusion about our hypothesis
is subject to two possible errors:
We may conclude that our hypothesis is true, when, in fact, it is false.
We may conclude that our hypothesis is false, when, in fact, it is true.

EXAMPLE: You may not be certain whether or not your lab section is meeting this week
If you decide to attend lab and the lab does not meet,
then you have made one type of error.
If you decide to skip lab when, in fact, the lab is meeting,
then you have made another type of error.
The consequences of these two errors are not the same.

A NULL HYPOTHESIS (Ho) is a hypothesis of
"no difference" or "no effect"

Scientists document an effect by rejecting Ho

Rejecting Ho when, in fact, it is true is a Type I (alpha) error.
Accepting Ho when, in fact, it is false is a Type II (beta) error.

The classic SCIENTIFIC METHOD proceeds by testing one,
or a series, of null hypotheses.
These confirmatory studies should be designed to minimize
Type I errors.
(by convention, a probability (P) of 0.05 is considered statistically
significant for rejecting Ho. This means that we reject
the null hypothesis with an alpha (Type I) of 5%)

Many scientific studies, however, are exploratory, rather than ,
confirmatory. These studies do not start with well-defined Ho.
Rather, they are useful for generating Ho for subsequent
confirmatory research.
Exploratory research should be designed to minimize Type II (beta) errors.

To be of any real value, the results of scientific inquiry must be
COMMUNICATED in a timely and effective manner.

Altlhough scientists can (and do) exchange ideas in a number of ways,
(e-mail, presentations at scientific meetings, etc.), PUBLICATION
remains the essential means of communication.

For maximum scientific value, publication should be in an appropriate
place, and should be neither premature nor long delayed.

Modern science is written in a very precise, yet concise, fashion.
Authors should avoid laboratory jargon, but should use appropriate
scientific vocabulary. Most scientific terms are derived from
Latin or Greek.

Tables, and, expecially, figures (graphs) are excellent ways of
presenting the results of scientific study.
BY CONVENTION (with only a few allowable exceptions), we plot
the "independent variable" (or the "cause", or the "treatment") on
the horizontal (X) axis, and the "dependent variable" (or the "effect",
or the "measurement" on the vertical (Y) axis."

Figures (graphs) are an effective way to REVEAL and DISPLAY
quantitative data.

....SEE EXAMPLES....

Keep in mind that some (perhaps much) of what you learn
in this course will eventually prove to be untrue.

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