Download Chapter 1 - Dr. Jennifer Capers

 Science refers to a body of knowledge
 Science is not a giant collection of facts to be
memorized.
 It important to learn about the process of science
called the scientific method.
 The scientific method allows the solving of
problems and answer questions.
 Observations
 Proposing ideas
 Testing the ideas
 Discarding or modifying ideas based on results
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1.1 The Process of Science
The Nature of Hypotheses
 Hypothesis: proposed explanation for a set of
observations
 Hypotheses needs to be:
 Testable – it must be possible to examine the
hypothesis through observations
 Falsifiable – it must be able to potentially be
proven false
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Where do hypotheses come from?
 Both logical and creative influences are used to
develop a hypothesis
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Scientific Theory
 Powerful, broad explanation of a large set of
observations
 Based on well supported hypotheses
 Supported by research from several different
independent sources
 As close to a “law” as you are going to get in
Biology
 Examples: Cell Theory, Evolutionary Theory
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The Logic of Hypothesis Tests
 Inductive reasoning: combining a series of
specific observations into a generalization to
create a hypothesis
 Use specifics to generalize
 For example: Dogs have hair. Dogs are mammals. Cats
have hair. Cats are mammals. Therefore, all mammals
must have lots of hair.
 Is that necessarily true?
 Can give a starting point to researching more
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The Logic of Hypothesis Tests
 To test the hypothesis use deductive reasoning:
 This involves using a general principle to predict
an expected observation using if/then statements
 For example, If vitamin C decreases the risk of
catching a cold, then people who take in additional
Vitamin C will get less colds.
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The Logic of
Hypothesis Tests
 The process looks
something like this:
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If people who
take vitamin C
suffer fewer
colds than
those who do
not. . .
If people who
take vitamin C
suffer the
same number
of colds or
more than
those who do
not. . .
Conclude that
prediction is
true
Conclude that
prediction is
false
Do not reject
the hypothesis
Reject the
hypothesis
Conduct
additional
tests
Why should scientists
consider alternative
hypotheses even if their
hypothesis is supported by
their research?
Consider
alternative
hypotheses
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Figure 1.3 (continued)
The Logic of Hypothesis Tests
 A hypothesis that fails our test is rejected and
considered disproven.
 A hypothesis that passes is supported, but not
proven.
 Why not? An alternative hypothesis might be the real
explanation.
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1.2 Hypothesis Testing
The most powerful way to test hypotheses: do
experiments!!
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Experiments support the hypothesis that the
common cold is caused by a virus.
(a) Cold–causing virus
(b) How the virus causes a cold
Nasal
passages
Host cell
1 Virus introduces its
genetic material into a
host cell.
Virus
Protein
shell
Throat
Genetic
material and
proteins
Virus
copies
2 The viral genetic material instructs the
host cell to make new copies of the
virus. Immune system cells target
infected host cells. Side effects are
increased mucus production and throat
irritation.
3 New copies of the virus are
released, killing host cell. These
copies can infect other cells in
the same person or cells in
another person (for example, if
transmitted by a sneeze).
Released
virus
copies
Immune
system cells
Mucus
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Figure 1.4
Find 2 steps in this process where drugs or therapies might
disrupt the infection, prevent spreading or lessen symptoms.
(a) Cold–causing virus
(b) How the virus causes a cold
Nasal
passages
Host cell
1 Virus introduces its
genetic material into a
host cell.
Virus
Protein
shell
Throat
Genetic
material and
proteins
Virus
copies
2 The viral genetic material instructs the
host cell to make new copies of the
virus. Immune system cells target
infected host cells. Side effects are
increased mucus production and throat
irritation.
3 New copies of the virus are
released, killing host cell. These
copies can infect other cells in
the same person or cells in
another person (for example, if
transmitted by a sneeze).
Released
virus
copies
Immune
system cells
Mucus
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Figure 1.4
The Experimental Method
 Experiments are designed to collect data or
information to test specific hypotheses.
 Variables: factors that can change in value under
different conditions
 Independent variables can be manipulated by the scientist
 In ideal experimental conditions, you only want to
manipulate 1 variable at a time – why?
 Dependent variables cannot be changed by
the researcher
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Controlled Experiments
 Controlled experiment: tests the effect of a
single variable
 Control: a subject who is not exposed to the
experimental treatment but has all other variables
the same
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Controlled Experiments
 Differences seen between the experimental
group and control group can be attributed to
the experimental treatment.
 Random Assignment
 An effective way of assigning individuals to
groups for testing
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Animation: Science as a Process: Arriving at Scientific Insights
Click “Go to Animation” / Click “Play”
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Controlled Experiments
 Example: Echinacea tea experiment:
 Hypothesis: drinking Echinacea tea relieves
cold symptoms
 Experimental group drinks Echinacea tea 5-6
times daily.
 Control group drinks “sham” Echinacea tea 5-6
times daily (placebo).
 Both groups rated the effectiveness of their
treatment on relieving cold symptoms.
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Controlled Experiments
 People who received
echinacea tea felt that
it was 33% more effective
at reducing symptoms.
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Minimizing Bias in Experimental Design
 If human subjects know whether they have received
the real treatment or a placebo, they may be biased.
 Blind experiment: subjects don’t know what kind of
treatment they have received
 Double blind experiment: the person
administering the treatments and the subjects do
not know who is in each gropu until after the
experiment is over
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Minimizing Bias in Experimental Design
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Using Correlation to Test Hypotheses
 The “gold standard” for experimentation
 Double-blind, placebo controlled and randomized
experiments
 Model systems can be used in experiments
when it appears to dangerous or unethical to test
on humans
 examples: mice, rats, dogs and pigs
 A correlation can be used to test hypotheses
when controlled experiments on humans is impossible to
perform
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Using Correlation to Test Hypotheses
 Using existing data, is there a correlation
between variables?
 Hypothesis: stress makes people more susceptible
to catching a cold
 Is there a correlation between stress and the number of colds
people have caught?
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Using Correlation to Test Hypotheses
 Results of such a study: the number of colds
increases as stress levels increase.
 Caution! Correlation does not imply causation.
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Using Correlation to Test Hypotheses
 The correlation might be due to other reasons.
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Overview: What Statistical Tests Can Tell Us
 Statistics in science is used to evaluate and
compare data.
 We can extend the results from small samples to an
entire population using statistical tests.
 Statistically significant: results of difference
between groups is due to random chance and not
an error in experimenting
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The Problem of Sampling Error
Sampling error: the effect of chance
 We can calculate the probability that a result is simply due to
sampling error.
Statistically significant: an observed difference
is probably not due to sampling error
Opinion polling before a recent election indicated
candidate A was favored by 47% of likely voters,
and candidate B was favored by 51% of voters.
There was a error of 3%. Why was this poll a
statistical tie?
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The Problem of Sampling Error
Confidence interval: the range of values from a
sample that has a 95% probability of containing the
true population mean (average).
Much population variation = large confidence
interval
Small population variation = small confidence
interval
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The Problem of
Sampling Error
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The one circled on the
left is better – see
how the red lines don’t
meet? You can say
with confidence that
there is a difference
Factors that Influence Statistical Significance
 Sample size
 The true difference between populations
 Bigger is better: more likely to detect differences
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Factors that Influence Statistical Significance
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A study followed 80,000 women over 20 years
Some ate lots of white flour and sugar, low vegetable fat and protein
Others ate low amounts of refined carbs, and more vegetables and
protein and had 30% less cases of heart disease
Where does this fall on chart?
What is the hypothesis? Difference between groups? Sample size?
Figure 1.15
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A study followed 80,000 women over 20 years
Some ate lots of white flour and sugar, low vegetable fat and protein
Others ate low amounts of refined carbs, and more vegetables and
protein and had 30% less cases of heart disease
Where does this fall on chart?
30%
80,000
women
Figure 1.15
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What Statistical Tests Cannot Tell Us
 If an experiment was designed and carried out
properly
 If observer error occurred, only can evaluate the
probability of sampling error
 May not be of any biological significance
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1.4 Evaluating Scientific Information
Primary Sources
 Researchers can submit a paper about their results
to a professional journal (primary source).
 Primary Sources undergo peer review: evaluation
of submitted papers by other experts
 Journal of Molecular Biology
 Journal of Biomedical Sciences
 Journal of Immunology
 Secondary sources: books, news reports, the
internet, and advertisements
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Information from Anecdotes
 Anecdotal evidence is based on one person’s
experience, not on experimental data.
 Example: a testimonial from a celebrity
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Science in the News
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Science in the News
 Secondary sources may be missing critical
information or report the information incorrectly.
 Consider the source of media reports.
 Be careful with the internet since anyone can
post information.
 Be very cautious about claims made in paid
advertisements.
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Understanding Science from Secondary Sources
 Use your understanding of the process of science to
evaluate science stories.
 News media generally highlight only those science
stories that seem newsworthy.
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1.5 Is There a Cure for the Common Cold?
 No, but prevention methods are known.
 Wash your hands!
 No effect on cold susceptibility:
 Vitamin C
 Exposure to cold temperatures
 Exercise
 No vaccine for the common cold
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Now let’s review with some questions:
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A(n) ________ is a proposed explanation for a single
observation.
scientific method
hypothesis
scientific theory
experiment
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Which of the following is a scientific hypothesis?
Jazz is better music than rap.
Garden fairies make tomatoes grow better.
Hunting species to extinction is wrong.
Increasing the amount of protein in a cow’s
diet increases her milk yield.
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Which of the following is correct?
A hypothesis can be wrong.
A hypothesis is not always testable.
A hypothesis can prove a person’s values.
A hypothesis should be formed before making any
observations.
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In an experiment, Dr. Smith feeds different amounts of
protein to dairy cows and measures the differences in
their milk yields. What is the independent variable?
time
milk yield
amount of protein
placebo
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What is happening in step #2 in the diagram?
The virus is
introducing its
genetic material
into the cell.
The host cell is
killed.
Copies of the virus
are being made by
the host cell.
The virus is being
destroyed by the
host cell.
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What does this graph show?
There is no difference
between placebo and
zinc lozenges.
Taking placebo
lozenges causes people
to have more types of
cold symptoms.
Zinc lozenges lead to
people catching fewer
colds.
People taking zinc
lozenges show cold
symptoms for a shorter
period of time.
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The confidence interval is the range of values that has a
_____ probability of containing the true population
mean.
5%
30%
75%
95%
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A statistical test evaluates the chance of __________.
observer error.
sampling error.
alternative mechanisms.
need for controls.
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Which of these statements about primary and
secondary sources are correct?
Primary sources are written by researchers;
secondary sources are written by book authors,
news reporters, and advertisers.
Primary sources aren’t biased; secondary sources
are biased.
Primary sources are not peer reviewed; secondary
sources are peer reviewed.
Primary sources are less reliable; secondary
sources are more reliable.
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What is the best way to prevent the common cold?
Take vitamin C.
Wash your hands.
Take zinc lozenges.
Get a cold vaccine.
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