13 The Scien Þc Method Lab 1 14 Lab 1 : Scien Þc Method 15 Introduc on What is science? You have likely taken several classes throughout your career as a student, and know that it is more than just chapters in a book. Science is a process that uses evidence to understand the history of the natural world and how it works. It is constantly changing as we understand more about the natural world, and con nues to advance the understanding of the universe. Science begins with ob- serva ons that can be measured in some way so that data can be collected in a useful manner by follow- ing the scien Þc method. Have you ever wondered why the sky is blue or why a plant grows toward a window? If so, you have al- ready taken the Þrst step down the road of discovery. No ma er what the ques on, the scien Þc meth- od can help Þnd an answer (or more than one answer!). Following the scien Þc method helps to insure scien sts can minimize bias when tes ng a theory. It will help you to collect and organize informa on in a useful way, looking for connec ons and pa erns in the data. As an experimenter, you should use the scien Þc method as you conduct the experiments throughout this manual. Concepts to explore: Testable observa ons Hypothesis Null hypothesis Experimental approach Variables Controls Data collec on Analysis Figure 1: The process of the scien Þc method Lab 1 : Scien Þc Method 16 The scien Þc method process begins with the formula on of a hypothesis – a statement of what the experimenter thinks will happen in certain situa ons. A hypothesis is an educated guess – a proposed explana on for an event based on observa on(s). A null hypothesis is a testable statement, that if proven true means the hypothesis was incorrect. Both statements must be testable, but only one can be true. Hypotheses are typically wri en in an if/ then format, such as: Hypothesis: If nutrients are added to soil, then plants grown in it will grow faster than plants without added nutrients in the soil. Null hypothesis: If nutrients are added to the soil, then the plants will grow the same as plants in soil without added nutrients. There are o en many ways to test a hypothesis. When designing an experiment to test a hypothesis there are three rules to follow: 1. The experiment must be replicable. 2. Only test one variable at a me. 3. Always include a control. Variables are deÞned and measurable components of an experiment. Controlling the variables in an experiment allows the scien st to quan tate the changes that occur so that results can be measured and conclusions drawn. There are three types of variables: Independent Variable: The variable that the scien st changes to a predetermined value in order to test the hypothesis. There can only be one independent variable in each experiment in order to pinpoint the change that a ects the outcome of the exper.

1. 13
The Scien Þc Method
Lab 1
14
Lab 1 : Scien Þc Method
15
Introduc on
What is science? You have likely taken several classes
throughout your career as a student, and know
that it is more than just chapters in a book. Science is a process
that uses evidence to understand the
history of the natural world and how it works. It is constantly
changing as we understand more about

2. the natural world, and con nues to advance the understanding of
the universe. Science begins with ob-
serva ons that can be measured in some way so that data can be
collected in a useful manner by follow-
ing the scien Þc method.
Have you ever wondered why the sky is blue or why a plant
grows toward a window? If so, you have al-
ready taken the Þrst step down the road of discovery. No ma er
what the ques on, the scien Þc meth-
od can help Þnd an answer (or more than one answer!).
Following the scien Þc method helps to insure
scien sts can minimize bias when tes ng a theory. It will help
you to collect and organize informa on in
a useful way, looking for connec ons and pa erns in the data. As
an experimenter, you should use the
scien Þc method as you conduct the experiments throughout this
manual.
Concepts to explore:
Testable observa ons
Hypothesis
Null hypothesis
Experimental approach

3. Variables
Controls
Data collec on
Analysis
Figure 1: The process of the scien Þc method
Lab 1 : Scien Þc Method
16
The scien Þc method process begins with the formula on of a
hypothesis – a statement of what the experimenter thinks will
happen in certain situa ons. A hypothesis is an educated guess
–
a proposed explana on for an event based on observa on(s). A
null hypothesis is a testable statement, that if proven true means
the hypothesis was incorrect. Both statements must be testable,
but only one can be true. Hypotheses are typically wri en in an
if/
then format, such as:
Hypothesis:

4. If nutrients are added to soil, then plants grown in it will
grow faster than plants without added nutrients in the soil.
Null hypothesis:
If nutrients are added to the soil, then the
plants will grow the same as plants in soil
without added nutrients.
There are o en many ways to test a hypothesis.
When designing an experiment to test a hypothesis
there are three rules to follow:
1. The experiment must be replicable.
2. Only test one variable at a me.
3. Always include a control.
Variables are deÞned and measurable components of an
experiment. Controlling the variables in an
experiment allows the scien st to quan tate the changes that
occur so that results can be measured
and conclusions drawn. There are three types of variables:
Independent Variable: The variable that the scien st changes to
a predetermined value

5. in order to test the hypothesis. There can only be one
independent variable in each
experiment in order to pinpoint the change that a ects the
outcome of the experi-
ment.
Dependent Variable: This variable is measured in regards to
condi ons of the inde-
pendent variable—it depends on the independent variable.
There can be more than
one dependent variable in each experiment.
If plants grow quicker when nutrients are added,
then the hypothesis is accepted and the null
hypothesis is rejected.
Figure 2: What a ects plant growth?
Lab 1 : Scien Þc Method
17
Controlled Variable: This variable, or variables (there could be
many) reßect the factors
that could inßuence the results of the experiment, but are not

6. the planned changes the
scien st is expec ng (by changing the independent variable).
These variables must be
controlled so that the results can be associated with some
change in the independent
variable.
When designing the experiment, establish a clear and concise
procedure. Controls must be iden Þed to
eliminate compounding changes that can inßuence the results.
O en mes, the hardest part of design-
ing an experiment is not Þguring out how to test the one factor
you focus on, but in trying to eliminate
the o en hidden inßuences that can skew results. Taking notes
when conduc ng an experiment is im-
portant, whether it is recording the temperature, humidity, me
of day, or another environmental con-
di on that may have an impact on the results. Also remember
that replica on is fundamental to scien-
Þc experiments. Before drawing conclusions, make sure your
data is repeatable. In other words, make
sure the experiment provides signiÞcant results over mul ple
trials.
O en, the best way to organize data for analysis is as a table or a
graph. Remember, any table or graph

7. should be able to stand on its own. In other words, another
scien st should be able to pick up the table
or graph and have all of the informa on necessary to interpret it,
with no other informa on.
Table: A well-organized summary of data collected. Only
include informa on relevant to the hypothesis
(e.g. don’t include the color of the plant because it’s not
relevant to what is being tested). Al-
ways include a clearly stated tle, label your columns and rows
and include the units of meas-
urement. For our example:
Table 1: Plant Growth With and Without Added Nutrients
Graph: A visual representa on of the rela onship between the
independent and dependent variable.
Graphs are useful in iden fying trends and illustra ng Þndings.
Rules to remember:
The independent variable is always graphed on the x-axis
(horizontal), with the depend-
ent variable on the y axis (ver cal).
Use appropriate numerical spacing when plo ng the graph, with
the lower numbers
star ng on both the lower and le hand corners.

8. Always use uniform or logarithmic intervals. For example, if
you begin by numbering, 0,
10, 20, do not jump to 25 then to 32.
Variable Height Wk1 (mm) Height Wk. 2 (mm) Height Wk. 3
(mm) Height Wk. 4 (mm)
Control
(without nutrients)
3.4 3.6 3.7
4.0
Independent
(with nutrients)
3.5 3.7 4.1 4.6
Lab 1 : Scien Þc Method
18
Title the graph and both the x and y axes such that they
correspond to the table from
which they come. For example, if you tled your table “Heart
rate of those who eat veg-
etables and those who do not eat vegetables”, be sure to tle the

9. graph the same.
Determine the most appropriate type of graph. Typically, line
and bar graphs are the
most common.
Line graph: Shows the rela onship between variables using plo
ed points that are connected with a
line. There must be a direct rela onship and dependence
between each point connected.
More than one set of data can be presented on a line graph.
Figure 3 uses the data from
our previous table:
Figure 3: Plant Growth, with and without Nutrients, over Time
Lab 1 : Scien Þc Method
19
Bar graph: Used to compare results that are independent from
each other, as opposed to a con nuous
series. Since the results from our previous example are con
nuous, they are not appropriate
for a bar graph.

10. Figure 4 shows the number of di erent kinds of birds observed
on a hike. Since there is no rela onship
between the di erent types of birds each result is independent
and a bar graph is appropriate.
Interpreta on: Based on the data you collected, is your
hypothesis supported or refuted? Based on the
data, is the null hypothesis supported or refuted? If the
hypothesis is supported, are there other varia-
bles which should be examined? For instance, was the amount
of water and sunlight consistent be-
tween groups of plants or, were all types of birds equally likely
to have been seen?
Figure 4: Number of Birds Seen on a Hike
Lab 1 : Scien Þc Method
20
Ac vity:
Dissolved oxygen is oxygen that is trapped in a ßuid, such as
water. Since virtually every living organism
requires oxygen to survive, it is a necessary component of water
systems such as streams, lakes and riv-

11. ers in order to support aqua c life. The dissolved oxygen is
measure in units of ppm - or parts per mil-
lion. Examine the data in Table 2 showing the amount of
dissolved oxygen present and the number of
Þsh observed in the body of water the sample was taken from;
Þnally, answer the ques ons below.
Table 2: Water Quality vs. Fish Popula on
1. Develop a hypothesis rela ng to the amount of dissolved
oxygen measured in the water
sample and the number of Þsh observed in the body of water.
2. What would your experimental approach be to test this
hypothesis?
3. What are the independent and dependent variables?
4. What type of graph would be appropriate for this data set?
Why?
5. Graph the data from Table 2.
Dissolved Oxygen (ppm) 0
Number of Fish Observed 0
2
1

12. 4
3
6
10
8
12
10
13
12
15
14
10
16
12
18
13
Lab Template
Week 1: Scientific Method

13. Submitted by: <your name here>
As you complete the lab, record your answers in this template.
Save the document as LastName_FirstName_BIO1020_W1A4,
and submit it to the Dropbox. Full lab instructions and the
rubric with which you will be evaluated can be found in the
online classroom.
Activity
Dissolved oxygen is oxygen that is trapped in a fluid, such as
water. Since virtually every living organism requires oxygen to
survive, it is a necessary component of water systems such as
streams, lakes and rivers in order to support aquatic life. The
dissolved oxygen is measure in units of ppm—or parts per
million. Examine the data in Table 2 showing the amount of
dissolved oxygen present and the number of fish observed in the
body of water the sample was taken from; finally, answer the
questions below.
Table 2: Water Quality vs. Fish Population
Dissolved Oxygen (ppm)
0
2
4
6
8
10
12
14
16
18
Number of Fish Observed
0
1
3

14. 10
12
13
15
10
12
13
Questions
1. Develop a hypothesis relating the amount of dissolved
oxygen measured in the water sample and the number of fish
observed in the body of water. (10 points)
2. What would your experimental approach be to test this
hypothesis? In other words, describe the experiment you would
carry out in order to test your hypothesis. (10 points)
3. What are the independent and dependent variables? (10
points)
4. What type of graph would be appropriate for this dataset?
Why? (10 points)

15. 5. Graph the data from the table above. Refer to the grading
rubric to ensure that your graph has all of the necessary
components. You can draw your graph by hand and scan it in,
or use the graphing tools in Microsoft Excel. (10 points)
Lab Hints
Week 1: Scientific Method
Before you start completing the Lab Template, quickly read
through the whole thing to get an idea of where you are going
with the activity. Now, do a quick plot of the data in Table 2.
This is just to help you visualize the data (tables are harder to
make sense of than graphs). I suggest to use the x (horizontal)
axis to plot 02 level and the y (vertical) axis to plot the number
of fish. If you plot each paired data point with a dot where the
02 level and the number of fish coincide, you will wind up with
dots going across the graph. Looking at the shape of the group
of dots will suggest whether you are looking at a difference
condition (where there is a sharp change) or a relationship
(where there is a more gradual change). If it seems to be a
relationship, is it a straight line relationship or do there appear
to be important points of 02 concentration when you see a shift
in fish population? Seeing this to begin with will help you think
through the rest of the questions.
Now let’s take a quick look at how to tackle each Question of

16. the Template:
Question 1: Based on our observations and thoughts about the
data, design a difference or relationship hypothesis that you can
test. Here are examples based on temperature and germination
rates in pinto beans (you only need to use one kind of
hypothesis depending on what you are noticing in the data).
Hypothesis (difference): There is no difference between the rate
of germination of pinto beans when germinated 40 degrees F
and 70 degrees F.
Hypothesis (relationship): There is no relationship between the
rate of germination of pinto beans and a series of temperatures.
Question 2: Design a simple way to put your hypothesis to the
test. This will require designing a way to collect data to
compare back to what your hypothesis predicts. Your results
will support or fail to support your hypothesis.The experiment
should be described in enough detail that someone else could
repeat the research in the same way.
Question 3: The independent variable is the one that is set in the
research design. The dependent variable is dependent upon the
state of the independent variable. Measurements or counts of
the dependent variable should change as the state of the
independent variable changes. Relative to the 02 and fish data,
which one seem to be dependent upon changes in the other?
Does 02 change because the number of fish changes or do the
number of fish change because the 02 is different in different
bodies of water?
Question 4. Several different kinds of graphs may be
appropriate depending on your research design. Don’t expect
there to be one right answer for everyone here.
Here is a link to a good resource on graphing and picking the
correct graph to use for specific kinds of data:
http://nces.ed.gov/nceskids/help/user_guide/graph/whentouse.as
p
Question 5. Include your graph of the data in Table 2 here. Be
sure to make sure you include all the necessary parts of a
correct graph format (as listed in the grading rubric for this

17. assignment).