Name_________________________________________
Period_______
Skills in Biology
Hypotheses and Predictions
Scientific knowledge grows through a process called the scientific method. This process involves observation and
measurement, hypothesizing and predicting, and planning and executing investigations designed to test formulated
hypotheses. A scientific hypothesis is a tentative explanation for an observation, which is capable of being tested
by experimentation. Hypotheses lead to predictions about the system involved and they are accepted or rejected
on the basis of findings arising from the investigation. Rejection of the hypothesis might lead to new alternative
explanations for the observations. Acceptance of the hypothesis as a valid explanation is not necessarily
permanent: explanations may be rejected at a later date in light of new findings.
Making Observations
These may involve the observation of behaviors in wild populations,
physiological measurements made during previous experiments or accidental
results obtained when seeking answers to completely unrelated questions.
Testing the Prediction
Asking Questions
The observations lead to the
formation of questions about
the system being studied.
The predictions are
tested out in the
practical part of an
investigation.
Formulating a Hypothesis
Features of a sound hypothesis:

It is based on observations and
prior knowledge of the system

It offers an explanation for an
observation.

It refers to only one
independent variable.

It is written as a definite
statement and not as a question

It is testable by experimentation

It leads to predictions about the
system.
Designing an investigation
Investigations are planned so
that the predictions about the
system made in the
hypothesis can be tested.
Investigations may be
laboratory or field based.
Making Predictions
Generating a Null
Hypothesis
A hypothesis based on observations
Based on a hypothesis,
predictions (expected,
repeatable outcomes) can be
generated about the behavior
of the system. Predictions may
be made on any aspect of the
material of interest, e.g. how
different variables (factors)
relate to each other.
is used to generate the null
hypothesis (Ho); the hypothesis of
no difference or no effect.
Hypotheses are expressed in the
null form for the purposes of
statistical testing. Ho may be
rejected in favor of accepting the
alternative hypothesis, HA.
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Developing Hypotheses
As questions are asked, scientists attempt to answer them by proposing possible explanations. Those proposed
explanations are called hypotheses. A hypothesis tentatively explains something observed. It proposes an answer
to a question. Consider question 5, preceding. One hypothesis based on this question might be “If spines on cacti
prevent animals from eating the cacti, then cacti will have spines.” The hypothesis has suggested a possible
explanation for the observed spines.
A scientifically useful hypothesis must be testable and falsifiable . To satisfy the requirement that a hypothesis is
falsifiable, it must be possible that the test results do not support the explanation. In our example, if spines are
removed from test cacti and the plants are not eaten by animals then the hypothesis has been falsified. Even
though the hypothesis can be falsified, it can never be proved to be true. The evidence from an investigation can
only provide support for the hypothesis. In our example, if cacti without spines were eaten, the hypothesis has not
been proved, but has been supported by evidence. Other explanations still must be excluded, and new evidence
from additional experiments and observations might falsify this hypothesis at a later date. In science seldom does a
single test provide results that clearly support or falsify a hypothesis. In most cases the evidence serves to modify
the hypothesis or the conditions of the experiment.
Science is a way of knowing about the natural world that involves testing hypotheses or explanations. The scientific
method can be applied to the unusual and the commonplace. You use the scientific method when you investigate
why your once white socks are now blue. Your hypothesis might be that your blue jeans and socks were washed
together, an assertion that can be tested through observations and experimentation.
Students often think that controlled experiments are the only way to test a hypothesis. The test of a hypothesis
may include experimentation, additional observations or the synthesis of information from a variety of sources.
Many scientific advances have relied on other procedures and information to test hypotheses. For example, James
Watson and Francis Crick developed a model that was their hypothesis for the structure of DNA. Their model could
only be supported if the accumulated data from a number of other scientists were consistent with the model.
Actually, their first model (hypothesis) was falsified by the work of Rosalind Franklin. Their final model was tested
and supported not only by the ongoing work of Franklin and Maurice Wilkins but also by research previously
published by Erwin Chargaff and others. Watson and Crick won the Nobel Prize for their scientific work. They did
not perform a controlled experiment in the laboratory but tested their powerful hypothesis through the use of
existing evidence from other research. Methods other than experimentation are acceptable in testing hypotheses.
Think about other areas of science that require comparative observations and the accumulation of data from a
variety of sources, all of which must be consistent with and support hypotheses or else be inconsistent and falsify
hypotheses.
The information in your biology textbook is often thought of as a collection of facts, well understood and correct. It
is true that much of the knowledge of biology has been derived through scientific investigations, has been
thoroughly tested, and is supported by strong evidence. However, scientific knowledge is always subject to novel
experiments and new technology, any aspect of which may result in modification of our ideas and a better
understanding of biological phenomena. The structure of the cell membrane is an example of the self-correcting
nature of science. Each model of the membrane has been modified as new results have negated one explanation
and provided support for an alternative explanation.
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Exercise 1.1
Questions and Hypotheses
This exercise explores the nature of scientific questions and hypotheses. A hypothesis offers a tentative
explanation to questions generated by observations. Hypotheses are often constructed in a form that allows them
to be tested statistically. For every hypothesis, there is a corresponding null hypothesis; a hypothesis against the
prediction. Predictions are tested with laboratory and field experiments and carefully focused observations. For a
hypothesis to be accepted it should be possible for anyone to test the predictions with the same methods and get a
similar result each time.
Part A—Asking Questions
Scientists are characteristically curious and creative individuals whose curiosity is directed toward
understanding the natural world. They use their study of previous research or personal observations of natural
phenomena as a basis for asking questions about the underlying causes or reasons for these phenomena. For a
question to be pursued by scientists, the phenomenon must be well defined and testable. The elements must be
measurable and controllable.
There are limits to the ability of science to answer question. Science is only one of many ways of knowing
about the world in which we live. Consider, for example, this question: Do excessively high temperatures cause
people to behave immorally? Can a scientist investigate this question? Temperature is certainly a well-defined,
measurable and controllable factor, but morality of behavior is not scientifically measurable. We probably could
not even reach a consensus on the definition. Thus, there is no experiment that can be performed to test the
question. Which of the following do you think can be answered scientifically? Place a check beside the questions
you think can be answered scientifically.
_______1. Does binge drinking cause more brain damage in teenagers than in adults?
_______2. Is genetically modified corn safe to eat?
_______3. Do children who wash their hands often and bathe daily have a greater risk of asthma than those who
wash their hands less often and bathe every other day?
_______4. Should endangered species be cloned to prevent extinction?
_______5. What is the function of spines on cacti?
_______6. Did the 19 year old college student develop ulcers because of his stress and fast food diet?
How did you decide which questions can be answered scientifically?__________________________
________________________________________________________________________________
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Part B – Developing Hypotheses
Before scientific questions can be answered, they must first be converted to hypotheses, which can be tested. For
each of the following questions, write an explanatory hypothesis. Recall that the hypothesis is a statement that
explains the phenomenon you are interested in investigating. For the purposes of our class, you will need to try to
state the hypothesis as an “if…then” statement.
1. Does regular interaction with pets improve the health of the elderly?
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2. What effect do high concentrations of the industrial pollutant PCB (polychlorinated biphenyl) have on killer
whale reproduction?
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Scientists often propose and reject a variety of hypotheses before they design a single test. Which of the following
statements would be useful as scientific hypotheses and could be investigated using scientific procedures? Give the
reason for each answer by stating whether it could possibly be falsified and what factors are measurable and
controllable.
1. The number of fungiform papillae (bumps on the tongue) affects taste sensitivity.
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2. Inflated self-esteem in young males increases the odds of aggression.
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3. Exposure to environmental pollutants produces feminization in newly hatched male
alligators.
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Exercise 1.2
Designing Experiments to Test Hypotheses
The most creative aspect of science is designing a test of your hypothesis that will provide unambiguous evidence
to falsify or support a particular explanation. Scientists often design, critique and modify a variety of experiments
and other tests before they commit the time and resources to perform a single experiment. In this exercise, you
will follow the procedure for experimentally testing hypotheses, but it is important to remember that other
methods, including observation and the synthesis of other sources of data, are acceptable in scientific
investigations. An experiment involves defining variables, outlining a procedure and determining controls to be
used as the experiment is performed. Once the experiment is defined, the investigator predicts the outcome of the
experiment based on the hypothesis.
Read the following description of a scientific investigation of the effects of sulfur dioxide on soybean reproduction.
Then in Lab Study A you will determine the types of variables involved, and in Lab Study B, the experimental
procedure for this experiment and others.
Investigation of the Effect of Sulfur Dioxide on Soybean Reproduction
Agricultural scientists were concerned about the effect of air pollution, sulfur dioxide in particular, on soybean
production in fields adjacent to coal powered plants. Based on initial investigations, they proposed that sulfur
dioxide in high concentrations would reduce reproduction in soybeans. They designed an experiment to test this
hypothesis (figure 1.1). In this experiment, 48 soybean plants, just beginning to produce flowers, were divided into
two groups, treatment and no treatment. The 24 treated plants were divided into four groups of six. One group of
6 treated plants was placed in a fumigation chamber and exposed to 0.6 ppm of sulfur dioxide for 4 hours to
simulate sulfur dioxide emissions from a power plant. The experiment was repeated on the remaining three
treated groups. The no treatment plants were placed similarly in groups of 6 in a second fumigation chamber and
simultaneously exposed to filtered air for 4 hours. Following the experiment, all plants were returned to the
greenhouse. When the beans matured, the number of bean pods, the number of seeds per pod, and the weight of
the pods were determined for each plant.
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Part A—Determining the Variables
Read the description of each category of variable; then identify the variable described in the preceding
investigation. The variables in an experiment must be clearly defined and measurable. The investigator will
identify and define dependent, independent and controlled variables for a particular experiment.
The Dependent Variable
Within the experiment, one variable will be measured or counted or observed in response to the experimental
conditions. This variable is the dependent variable. For soybeans, several dependent variables are measured, all of
which provide information about reproduction. What are they?
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The Independent Variable
The scientist will choose one variable, or experimental condition, to manipulate. This variable is considered the
most important variable by which to test the investigator’s hypothesis and is called the independent variable.
What was the independent variable in the investigation of the effect of sulfur dioxide on soybean
reproduction?__________________________________________________________________________________
______________________________________________________________________________________________
Can you suggest other variables that the investigator might have changed that would have had an effect on the
dependent variables?____________________________________________________________________________
______________________________________________________________________________________________
Although other factors, such as light, temperature, time and fertilizer, might affect the dependent variables, only
one independent variable is usually chosen. Why is it important to have only one independent variable?
_____________________________________________________________________________________________
_____________________________________________________________________________________________
Why is it acceptable to have more than one dependent variable?________________________________________
______________________________________________________________________________________________
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The Controlled Variable or Constants
Consider the variables that you identified as alternative independent variables. Although they are not part of the
hypothesis being tested in this investigation, they would have significant effects on the outcome of this experiment.
These variables must, therefore, be kept constant during the course of the experiment. They are known as the
controlled variables. The underlying assumption in experimental design is that the selected independent variable
is the one affecting the dependent variable. This is only true if all other variables are controlled.
What are the controlled variables in this experiment?
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What variables other than those you may have already listed can you now suggest?
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Part B—Choosing or Designing the Procedure
The procedure is the stepwise method, or sequence of step, to be performed for the experiment. It should be
recorded in a laboratory notebook before initiating the experiment and any exceptions or modifications should be
noted during the experiment. The procedures may be designed from research published in scientific journals,
through collaboration with colleagues in the lab or other institutions, or by means of one’s own novel and creative
ideas. The process of outlining the procedure includes determining control treatment(s), levels of treatments and
numbers of replications.
Level of Treatment
The value set for the independent variable is called the level of treatment. For this experiment, the value was
determined based on previous research and preliminary measurements of sulfur dioxide emissions. The scientists
may select a range of concentrations from no sulfur dioxide to an extremely high concentration. The levels should
be based on knowledge of the system and the biological significance of the treatment level. What was the level of
treatment in the soybean experiment?
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____________________________________________________________________________________________
Replication
Scientific investigations are not valid if the conclusions drawn from them are based on one experiment with one or
two individuals. Generally, the same procedure will be repeated several times (replication), providing consistent
results. Notice that scientists do not expect exactly the same results inasmuch as individuals and their responses
will vary. Results from replicated experiments are usually averaged and may be further analyzed using statistical
tests. Describe replication in the soybean experiment.
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______________________________________________________________________________________________
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Control or Control Group
The experimental design includes a control in which the independent variable is held at an established level or is
omitted. The control or control treatment serves as a benchmark that allows the scientist to decide whether the
predicted effect is really due to the independent variable. In the case of the soybean experiment, what was the
control treatment?
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What is the difference between the control and the controlled variables discussed previously?
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Part C—Writing Hypotheses
When rigorous science is conducted, experimental design generally includes a Null Hypothesis as well as
Alternative Hypotheses. A Null Hypothesis is one that can be tested statistically and generally states that there is
no effect on the experimental organisms when exposed to the treatment. The Alternative Hypothesis predicts
what the investigator thinks will happen in the experiment. The prediction is always based on the particular
experiment designed to test a specific hypothesis. Hypotheses/Predictions are written in the form of if/then
statements: “If [the independent variable] does this, then the [dependent variable] does this” For example, “if
cactus spines prevent herbivory, then removal of the spines will result in cacti being eaten by animals.” Making a
prediction provides a critical analysis of the experimental design. If the predictions are not clear, the procedure can
be modified before beginning the experiment. For the soybean experiment, the idea being tested was: “Exposure
to sulfur dioxide reduces reproduction.” State the Null Hypothesis and an Alternative Hypothesis.
Null (HO):
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Alternative (HA):
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To evaluate the results of the experiment, the investigator always returns to the prediction. If the results match the
prediction, then the hypothesis is supported. If the results do not match the prediction, then the hypothesis is
rejected. Either way, the scientist has increased knowledge of the process being studied. Many times the rejection
of a hypothesis can provide more information than confirmation, since the ideas and data must be critically
evaluated in light of new information. In the soybean experiment, the scientist may learn that the prediction is true
(sulfur dioxide does reduce reproduction at the concentration tested). As the next step, the scientist may now wish
to identify the particular level at which the effect is first demonstrated.
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Calculation of Descriptive Statistics
1. A survey of the number of spores found on the fronds of a fern plant was conducted. The data is
listed below:
Raw data: Number of spores per frond
64
60 64 62 68 66 63
69
70 63 70 70 63 62
71
69 59 70 66 61 70
67
64 63 64
Calculate each of the following—show work for all!
a. Mean
b. Median
c. Mode
d. Range
e. Standard deviation
Page 9 of 15
Practice
A student investigated the variation in the length of bivalve shells at two
locations on a rocky shore.
Show ALL WORK!!!
State the Null Hypothesis:
State an Alternative Hypothesis:
Data Collected
Shell Length in mm
Group A
Group B
46
23
50
28
45
41
45
31
63
26
57
33
65
35
73
21
55
38
79
30
62
36
59
38
71
45
68
28
77
42
Complete the table below:
Group A
Mean
Median
Mode
Range
SE
**95% CI
Group B
**CI = mean ± (SE x 2)
Page 10 of 15
Based on the statistics on the previous page, should you accept or reject the Null Hypothesis? Explain.
Based on the statistics calculated on the previous page, what can you conclude?
What does this data and the statistics tell us about the two sets of bivalves and their environment?
Page 11 of 15
The Chi Square Test
This is a statistical test used to compare observed results with expected results. The calculation generates a X2
value. The higher the value of X2 the greater the difference between the observed and expected results.
Use this test when:
The measurements relate to the number of individuals in a particular category
The observed number can be compared with an expected number which is calculated from theory
How to use a Chi Squared Test:
1. State the Null Hypothesis
a. This statement says that there is no statistical difference between the observed and expected
results
2. Calculate the expected value
a. This may be the mean of the expected values
b. When you study inheritance, you would add up the expected values and apply a ratio
3. Calculate the Chi Squared value
(𝑜 − 𝑒)2
∑
𝑒
Where O = observed value
E = Expected value
4.
5.
6.
Determine the degrees of freedom
a. This is calculated from the formula n-1 where n = the number of sets of results
b. This basically measures how many classes of results can freely vary in their numbers. For example,
if you were tossing two coins at a time and had an accurate count of how many 2 heads and 2 tails
tosses were observed, then you already know how many of the 100 tosses ended up as mixed
head-tails, so the third measurement provides no additional information.
Compare the Chi Squared value against a table of critical values.
a. Refer to the degrees of freedom
b. Look up the chi-square value you calculated on the table below.
c. Use the table to determine the p value.
Decide whether to accept or reject the Null Hypothesis.
a. If the p value is greater than .05 then you would accept (fail to reject) your null hypothesis .
b. If the p value is .05 or less then you would reject your null hypothesis.
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7.
Draw a conclusion.
a. The Null hypothesis states that there is no difference between your observed and expected results.
b. If p ≤ .05 then Null Hypothesis is Rejected.
i. This means that if the difference between your observed data and your expected data
would occur due to chance alone fewer than 1 time in 20 (p=.05) then there is a 95%
chance that the differences between your observed and your expected data are due to
some other factor beyond chance.
ii. This means there is a statistically significant difference between what you expected and
what you observed and you would reject your null hypothesis.
c. If p>.05 then the Null Hypothesis is Accepted.
i. This means that there is no statistical difference between the observed and expected
results.
ii. Any difference between the observed and expected results are due to random events and
doesn’t represent any sort of biological phenomenon.
Page 13 of 15
Chi Square Practice
Naked mole rats are a burrowing rodent native to parts of East Africa. They have
a complex social structure in which only one female (the queen) and one to three
males reproduce, while the rest of the members of the colony function as
workers. Mammal ecologists suspected that they had an unusual male to female
ratio. They counted the numbers of each sex in one colony.
Sex
Female
Male
Number of Animals
52
34
State the Null Hypothesis:
What is the sex ratio you would EXPECT in the population?
Calculate the Chi Squared Value below:
Sex
Observed
Female
52
Male
34
Total
Expected
o-e
(o-e)2
(o-e)2/e
X2 ___________
What are the degrees of freedom? _________
Based on the degrees of freedom and calculated Chi Squared value what is the p value? (LOOK IT UP ON THE TABLE)
___________
Properly state your conclusion below based on the p value.
Page 14 of 15
Chi Squared Practice
You have been wandering about on a seashore and you have noticed that
a small snail (the flat periwinkle) seems to live only on seaweeds of
various kinds. You decide to investigate whether the animals prefer
certain kinds of seaweed by counting numbers of animals on different
species. You end up with the following data:
Type of Seaweed
Number of animals on
each kind of seaweed
Serrated wrack
45
Bladder wrack
38
Egg wrack
10
Spiral wrack
5
Other algae
2
TOTAL 100
State the Null Hypothesis:
What proportions would you EXPECT to see of each seaweed?
Calculate the Chi Squared Value below:
Seaweed
Observed
Serrated wrack
Bladder wrack
Egg wrack
Spiral wrack
Other algae
Total
Expected
o-e
(o-e)2
(o-e)2/e
45
38
10
5
2
100
X2 ___________
What are the degrees of freedom? _________
Based on the degrees of freedom and calculated Chi Squared value what is the p value? (LOOK IT UP ON THE TABLE)
___________
Properly state your conclusion below based on the p value.
Page 15 of 15