Lab 2: Thinking like a Scientist

Thinking Like a ScientistInquiries into the Scientific Method
Science is not a collection of facts, but a process we can use to understand the world. The scientific
method is a techniques for investigating phenomena and acquiring new knowledge, as well as for
correcting and integrating previous knowledge. It is based on gathering observable, empirical,
measurable evidence, subject to the principles of reasoning.
Although procedures vary from one field of inquiry to another, there are identifiable features that
distinguish scientific inquiry from other methods of developing knowledge (figure 1). Scientific
researchers propose specific hypotheses as explanations of natural phenomena, and design
experimental studies that test these predictions for accuracy. These steps are repeated in order to
make increasingly dependable predictions of future results. Science is designed to test hypothesis,
but only has the power to prove something false, it can’t prove something is true. We come to an
idea about the ‘truth’ by testing hypothesis over and over again, trying to prove them wrong. If we
continue this process for long enough, we may come to have great confidence in our ideas and call
it a theory (such as gravity, electricity, evolution, atomic structure, etc). The best way to understand
science and the scientific method is to practice it.
In today’s lab we will practice thinking like a scientist by doing four different experiments which
help us practice different parts of the scientific method.
Figure 1. The steps of the Scientific Method.
Part 1. The Weight of Water
Goals: Gain practical experience with glassware, laboratory balances, experimental design and
descriptive statistics. Today will be our first experience in how doubt and skepticism are part of the
scientific endeavor.
We will show you three different kinds of laboratory glassware. All of them have graduations
showing 100ml. Your mission is to determine which one is most appropriate for measuring exactly
100ml of water. Water has a density of 1.0 g/ml. This means that 100ml of water should weigh 100
1. First develop a hypothesis as to which one will be the most accurate and precise and write it
down. Your idea should include a justification-why is it that you think this one is more
precise than another.
One very important part of science is our ability (or lack there of) to generalize from a relatively
small data set. You’ll want to make your measurements three times on each type of glassware, this
is what we call a replicate. You’ll report the mean (average) of each type of glassware.
You will use the laboratory balances-Do not get water on them. In order to determine the mass of
water in a container, you must first weigh the dry container, fill the container, weigh the container
and water, and then subtract off the mass of the container. You’ll want to do this for each piece of
glassware. Don’t assume that each beaker (or other glassware) has the same mass, weigh them all
Consistency is one of the most important skills in the lab and in all scientific investigations. You
must fill your glassware exactly the same way each time. I will demonstrate how to fill them to the
right level. You may want to use pipettes to add to your glassware a drop at a time.
2. Once finished with your measurements, calculate mean (average) for each type of glassware.
3. Conclusion: Please write a paragraph in which you address the following: You may do this
in pairs.
A) Describe the class data.
B) Did your data validate your hypothesis? How?
C) Did the class data validate your hypothesis (i.e. were the class data the same as yours)?
D) What do the class data indicate regarding which type/s of glassware are good for accurate and
precise measurements and which would you use if you needed approximately 100ml?
E) Were your data the same or similar to that of your classmates? If yours were different, justify
(develop a logical argument as to) why this might be so.
F) Are some of the class data clearly different than the rest? Whose data should we believe and
The Weight of Water- Data Table
You may find this table a convenient way to organize your data.
+ H2O
+ H2O
Flask +
Part 2. Thinking Inside the Box
Thinking Inside The Box Conference
Dear Fellow Box Researcher:
It is my pleasure to invite you and the members of your research group to attend the First
Annual "Thinking Inside The Box" Conference. We would like you to present the results
of your investigative studies on the contents of The Box.
A reminder of the ground rules for these studies:
1. Investigators must, to the best of their ability, describe the contents of The Box.
2. The Box may never be opened; the contents may NOT be looked at.
We look forward to your presentation at this conference.
Chester Intrados
Conference Chair
You are working in your office at GenChemCo Industries one day when the above letter arrives.
Of course, you had forgotten about your earlier commitment to assist The Box Studies Department
in their quest towards a better understanding of the contents of The Box. So, you locate The Box
sample that had been given to you and quickly gather your research group together.
I. The Research Group Study
"We've been invited to attend the Thinking Inside The Box Conference," you tell your group. "Let's
see what we can do to put together a presentation for the conference. We need to describe the
contents of The Box, but we may not open The Box or in any way look at its contents. Our goal is to
characterize the contents, not guess what they are."
As a group, pass The Box around to each member of your research team, and begin to record and
organize your observations. You, as the leader of your research group, should direct this
II. The Conference
A member from each research group (not the leader or the recorder) will be asked to make a formal
presentation to the conference on their group's findings. This presentation should summarize your
findings and should not be a simple list of observations. You will record your findings on the
board. The conference chair will act as a recorder.
III. The Agency
Each group will have five minutes to prepare a short research proposal. This proposal should
indicate what, experimentally, is to be performed and what results might be expected. Each group
will make their presentations to the conference. The conference will act as a review panel, with
each member of the conference "voting" for his/her favorite proposal (an individual may not vote
for his/her group's proposal). The two proposals with the greatest amount of support will be funded.
Part 3. The 2 Liter Flush
Task: You need to find the fastest way to get water out of 2-liter bottle.
Objective: Test 3 methods of emptying the bottle to find out which is the quickest
Plastic bottle
Bucket to collect water
Stop watch
Fill bottle with water up to the neck of the bottle
Dump water into bucket (carefully), repeat.
Before you start:
1. Design your experimental procedures, thinking of three methods for getting the water out of
the bottles.
2. Write a Hypothesis about which method will be the best/fastest.
3. Write out your Methods which you’ll use.
After Experiments:
4. Record your Results and graph them for easy interpretation.
5. Discuss your results
6. Form a Conclusion answering your proposed hypothesis.
Data Table for 2-liter Flush. Record your time trials in seconds.
Method 1
Method 2
Replicate 1
Replicate 2
Replicate 3
Average time
Method 3
Part 4. Hypothetical Study Design
Observations: You are a medical researcher developing a weight-loss drug. The rats you use as
test subjects lose weight just fine, however, the autopsies of some of them show heart valve
damage. Use the "Vocabulary of Experiments" section below, and your own understanding of the
scientific method, to design a study to determine if your drug is causing the heart valve damage.
Not all of the vocabulary terms may apply to your experiment.
You need to take the observations and design an experiment. You will also make up the resulting
data of that experiment and graph that data (or summary of data). Your conclusions should follow
logically from your data and must address the question posed in the observation. Introduce the
question and observations, explain your methods, explain your results, and have a clear conclusion.
Make sure issues like replication and controls are adequately addressed.
Independent variable:
Dependent variable:
Control variables:
Experimental group:
Control group:
Vocabulary of Experiments
Experiments are organized and systematic attempts to coax information out of nature. They
are often attempts to investigate and/or establish a causal relationship between two variables (i.e.
cigarette smoking and cancer). For the sake of illustration, we will assume that we are agricultural
scientists who have recently invented a new “green” fertilizer. We want to understand how it might
be used to help a farmer increase our corn yield.
Hypothesis: Typically a proposed explanation for the effect of the independent variable. These are
very specific.
Null hypothesis: The independent variable causes has no affect on the dependent variable.
Variable: Something that changes or that may be manipulated (the addition of our fertilizer,
amount of fertilizer, water, light, temperature, soil, etc).
Independent variable: The variable that the scientist changes or manipulates (our fertilizer).
Dependent variable: The variable that changes in response to the independent variable (yield of
Control variable: These are all the variables that the scientist endeavors to hold constant such that
she knows that the change in the dependent variable is resultant of the independent variable (include
things such as amount of water, soil type, light conditions, growing season, etc.).
Experimental group: This is the set of experimental subjects that is exposed to the independent
variable (corn plants that get the fertilizer).
Control group: This is the set of experimental subjects that is kept under exactly the same
conditions as the experimental group but does not receive the independent variable (corn plants that
do not receive the fertilizer).
Replicate: Typically scientists don’t just run one experimental subject or group, we run several
(three or more) replicates so that we can compare them. If we ran just one we would not be able to
detect anomalous results that might arise from contamination or some other factor (several different
plots of corn. One might argue using several different corn plants, but replicates typically consist of
several groups with many different plants).
Treatment: Treatments are typically different applications of the independent variable. We might
devise an experiment to test the effect of several different concentrations or applications of our
independent variable (fertilizer).