This document discusses what science is and is not. It begins by stating that science attempts to disprove ideas rather than prove them, and is concerned with understanding the natural world through observation and experimentation. It notes several misconceptions, such as the idea that science can prove anything or that there is a linear progression from hypothesis to theory to law. Good science minimizes bias through random sampling, appropriate measurement techniques, and independent verification. It emphasizes that science provides the most reliable knowledge about the natural world but does not claim certainty, only degrees of probability. Overall, the document provides a concise overview of the scientific process and addresses common misconceptions about the limitations and objectives of science.
2. What is Science?
or
1. Science is concerned with
understanding how nature and the
physical world work.
2. Science can prove anything, solve
any problem, or answer any
question.
3. Any study done carefully and
based on observation is scientific.
4. Science can be done poorly.
5. Anything done scientifically can
be relied upon to be accurate and
reliable.
3. What is Science?
or
6. Different scientists may get
different solutions to the
same problem.
7. Knowledge of what science is,
what it can and cannot do,
and how it works, is
important for all people.
8. A hypothesis becomes a
theory which becomes a law.
9. A hypothesis is an educated
guess.
10. A general and universal
scientific method exists.
4. 1. Science is concerned with understanding
how nature and the physical world work.
5. • Science actually attempts to disprove ideas
(hypotheses).
• Science is limited strictly to solving problems
about the physical and natural world.
• Explanations based on supernatural forces,
values or ethics can never be disproved and
thus do not fall under the realm of science.
2. Science can prove anything, solve any
problem or answer any question.
6. 3. Any study done carefully and
based on observation is scientific.
• Science must follow certain rules.
• The rules of science make the scientific
process as objective as is possible.
Objective = Not influenced by feelings,
interests and prejudices; UNBIASED
vs.
Subjective = Influenced by feelings,
interests and prejudices; BIASED
7. 4. Science can be done poorly.
• Science can be done poorly, just like any
other human endeavor.
• Quality control mechanisms in science
increase the reliability of its product.
5. Anything done scientifically can be relied
upon to be accurate and reliable.
8. 6. Different scientists may get different
solutions to the same problem.
• Results can be influenced by the race, gender,
nationality, religion, politics or economic
interests of the scientist.
• Sampling or measurement bias can result in
different solutions to the same problem.
9. 7. Knowledge of what science is, what it can
and cannot do, and how it works, is important
for all people.
10. 8. A hypothesis becomes a theory
which becomes a law.
• Major misconception
• There is not a natural progression
from hypothesis to theory to law
• This myth deals with the general
belief that with increased evidence
there is a developmental
sequence through which scientific
ideas pass on their way to final
acceptance
11. 9. A hypothesis is an educated guess.
• A hypothesis is a testable statement based
upon research
• Most of the time in science class, students
are asked to propose a hypothesis during a
laboratory experience, but they are actually
giving a prediction.
• As for those hypotheses that are really
forecasts, perhaps they should simply be
called what they are, predictions.
12. 10. A general and universal
scientific method exists.
• Scientists approach and solve problems with
imagination, creativity, prior knowledge and
perseverance.
• These are the same methods used by all
problem-solvers.
• The lesson to be learned is that science is no
different from other human endeavors when
puzzles are investigated.
13. So, What is Science?
• Modern science is a process by which we try
to understand how the natural world works
and how it came to be that way.
• It is NOT a process for merely collecting
"facts" about, or just describing, the natural
world, although such observations do provide
the raw material for scientific understanding.
• There is no certainty in science, only
degrees of probability (likelihood), and
potential for change.
15. What is Science?
• Scientific understanding can always be
challenged, and even changed, with new
ways of observing, and with different
interpretations.
• The same is true of scientific facts.
• New tools, techniques, and advances in
technology have resulted in new
observations, sometimes forcing revision of
what had been taken as fact in the past.
16. Why is science so useful?
• Scientific knowledge is the most
reliable knowledge we have about
the natural world.
• Science has enabled much of our
work in space exploration, modern
medicine, agriculture, and
technology
17. Objectivity is the key to good science.
To be objective, experiments need to be
designed and conducted in a way that
does not introduce bias into the study.
What is good science?
18. Two types of bias:
1. Sampling bias
2. Measurement Bias
Bias = A prejudiced presentation of material
19. Sampling Bias
Sample = A group of units selected to be
“measured” from a larger group (the
population).
Sampling bias is introduced when the
sample used is not representative of the
population or inappropriate for the question
asked.
20. 1. Use a RANDOM SAMPLE = every individual
has an equal likelihood of being chosen.
2. Limit the question asked to the specific group
sampled.
SAMPLE SIZE: Is the sample big enough to get a good
average value?
SELECTION OF SAMPLE: Does the composition of the
sample reflect the composition of the population?
Factors that contribute to sampling bias
Factors such as location, age, gender, ethnicity, nationality
and living environment can affect the data gathered.
How to minimize sample selection bias:
21. Measurement Bias
Is the method of data collection chosen in such a
way that data collected will best match reality?
Evaluate the technique:
• Measurements taken accurately
• No additions to the environment that
will influence results
• Experiment designed to isolate the
effect of multiple factors
22. Good science depends on a well-designed
experiment that minimizes bias by using the
appropriate:
•Sample size
•Sample selection
•Measurement techniques
***for the question being investigated
Summary
23. Identifying good science: Look for signs of bias!
• Language
• Appropriate data reported to back
conclusions
• Data source
24. Language
“Scientifically-proven”
* Science does not seek to prove but to disprove
* Be suspicious of this claim!
Emotional appeals
* Conclusions should be data-based
* Emotional appeals usually are not data-based
Strong language
* Scientific conclusions should only report what the
data supports.
* Words should be chosen very carefully to avoid
exaggeration or claims not supported by data.
THE DATA SHOULD CONVINCE YOU,
NOT THE WORDS USED!
25. Appropriate data reported to back
conclusions
Are samples and measurements appropriate
for the conclusion presented?
Are multiple factors properly accounted for
to justify the interpretation of the data?
26. Data Sources
All organizations should produce unbiased data.
However, it is important to understand the
organization’s motivation to be able to identify
potential bias. In some situations, the need to
promote special interests or make profits may lead
to bias.
1. University Research
2. Corporate Research
3. Government Research
4. Research by Special
Interest Groups
27. The Effects of Teen Smoking
Examining the Data Source
Investigations of Passive Smoking Harm:
Relationship between Article Conclusions & Author Affiliations
Number (%) of Reviews
Article Conclusion Tobacco
Affiliated
Authors (n=31)
Non-Tobacco
Affiliated Authors
(n=75)
Passive smoking harmful 2 (6%) 65 (87%)
Passive smoking not
harmful
29 (94%) 10 (13%)
Significance
Χ2
=60.69; P<.001
Barnes, Deborah E. 1998. Why review articles on the health effects of
passive smoking reach different conclusions. JAMA. 279(19): 1566-1570.
28. •Independent duplication = Two or more
scientists from different institutions investigate the
same question separately and get similar results.
•Peer-reviewed journal = A journal that publishes
articles only after they have been checked for
quality by several expert, objective scientists from
different institutions.
The scientific community engages in
certain quality control measures to
eliminate bias.
Results are verified by independent duplication
and publication in a peer-reviewed journal.
29. Scientists:
• Learn to question
• Do not prejudge
• Have an open mind to topics
• Realize there is more that you do not know,
than what you do know
30. Quote of the Day:
• Theories are nets to catch what we call
“the world:” to rationalize, to explain,
and to master it. We endeavor to make
that mesh finer and finer.”
– Karl Popper (1935)
Editor's Notes
This slide contains the 8 true/false questions that compose the Opening Questions section in the student workbook. It can be displayed while students work on answering the questions.
Science is primarily concerned with understanding how the physical world works.
True.
Science is a process by which we try to understand how the physical world works and how it came to be that way. The physical world includes the world we can observe with our senses with or without technological aids.
Science can prove anything.
FALSE.
The process of science, when properly applied, actually attempts to disprove ideas (hypotheses) by testing or challenging the hypothesis with observations (data) gathered from carefully designed experiments. If the idea survives testing, then it is stronger, and more likely an accurate explanation. Science is a process which can only produce “possible” or “highly probable” explanations for natural phenomena; these are never certainties. With new information, tools, or approaches, earlier findings can be replaced by new findings.
Science can solve any problem or answer any question.
FALSE.
The realm of science is limited strictly to solving problems about the physical world, a world that we can observe with our senses. Science is not properly equipped to handle the supernatural realm, nor the realm of values and ethics, realms that cannot be observed with our senses. Scientific explanations must be potentially disprovable. Explanations based on supernatural forces, values or ethics can never be disproved and thus do not fall under the realm of science.
Any study done carefully and based on observation is scientific.
FALSE.
Science must follow certain rules; otherwise, it&apos;s not science (just as soccer is not soccer if its rules are not followed). The rules of science are intended to make the process as objective as is humanly possible, and thereby produce a degree of understanding that is as close to reality as possible. Scientific explanations must be based on careful observations and the testing of hypotheses.
Define objective
Science can be done poorly.
TRUE.
Anything done scientifically can be relied upon to be accurate and reliable.
FALSE.
Science can be done poorly, just like any other human endeavor. We are all fallible, some of us make fewer mistakes than others, some observe better than others, but we are still subjective in the end. Self-correction mechanisms in science increase the reliability of its product.
Different scientists may get different solutions to the same problem.
Science can be influenced by the race, gender, nationality, religion, politics or economic interests of the scientist.
TRUE.
Intentional or unintentional sources of bias introduced in a study can result in different solutions to the same problem. Scientists are people, and although they follow certain rules and try to be as objective as possible, both in their observations and their interpretations, their biases are still there. Unconscious racial bias, gender bias, social status, source of funding, or political leanings can and do influence one&apos;s perceptions and interpretations.
Unfortunately, science is all too frequently misused. Because it works so well, there are those who apply the name of science to their efforts to &quot;prove&quot; their favorite cause, even if the rules of science were not followed. Such causes are properly labeled &quot;pseudosciences&quot;. Also, some scientists have been known to do fraudulent work, in order to support their pet ideas. Such work is usually exposed sooner or later, due to the peer review system and the work of other scientists.
Knowledge of what science is, what it can and cannot do, and how it works, is important for all people.
People need to be able to evaluate scientific information and make decisions about the information. Scientific information is used to support political arguments, advertise products, and inform people of factors that affect their health. It is important for all people to be scientifically literate in order for them to be able think critically about what to vote for, what to buy and how to protect their health.
Given that science can be poorly done, what is good science?
Discuss these examples to help explain the way these different factors can cause sampling bias.
Sample Size:
Ex. To determine the average height of students in this classroom, how many students should I measure to get the best estimate? If I only measure 3 will my mean be accurate?
Sample Selection:
Factors such as location, age, gender, ethnicity, nationality and living environment can affect the data gathered for a sample. A good experiment controls for these factors by using a random sample or by limiting the question asked to the specific group represented by the sample.
Random sample = Samples drawn in such a way that every individual has an equal likelihood of being selected.
Example of random sample: Rolling dice, flipping a coin
Example of sample selection bias:
I want to find the average height of students in the classroom. I notice a list of students that are to be excused early because they are on the basketball team and have a game. I decide to use this list to pick the students that will be in my sample. How might this method of selecting my sample bias my estimate of average height?
What are factors that contribute to sampling bias?
What are some ways to minimize sampling bias?
Discuss these examples to help explain the way measurement technique can cause measurement bias.
Use measurement tool correctly
Ex. When measuring height, I must be careful to start the measuring tape at exactly at 0, not at 1 cm.
No additions to the environment that will influence results
Ex. I take height measurements of everyone in the classroom and let them keep their shoes on. All shoes add height, some more than others, and this will change the measure I get for average height.
Experiment designed to separate out the affect of multiple factors
Ex. I propose the hypothesis that students that sleep more than 7 hours the night before a test will perform better on the test. I ask students to report how much sleep they received the night before on their tests and compare this with their test scores. I do not ask or control for other factors such as how much each student studied or whether they ate breakfast. How can I know that any trend I observe is reflective of how much sleep they received and not other factors?
What are 3 factors that contribute to measurement bias?
What are some clues that scientific information you are reading is biased?
Discuss examples for evidence of bias.
1. Emotional appeal – gives emotional reasons for believing or not believing the scientific
conclusions. “People will senselessly die unless we use Vacinax now!”
2.“scientifically-proven” – science sets out to disprove, not prove things. Thus anytime
you encounter the phrase “scientifically-proven”, be suspicious.
3. Identify strong language – “cleanest”, “cheapest”, “ most efficient”, “in the world”
For each point you can use the examples used previously:
Are sample and measurements appropriate for the conclusion presented?
Ex. Determining average height in classroom using basketball team or taking measurements with shoes on.
Are multiple factors properly accounted for to justify the interpretation of the data?
Ex. Correlation between sleep and test results.
You may want to highlight that there are plenty of examples of both good and bad research done by all of these groups. A careful understanding of the interests and funding sources of research will give you an idea of what the bias might be if the research is biased. However, even if a scientist has an interest in getting certain results it does not mean that their research will be biased. If they are a good scientist, they will be true to the scientific process and they will design good experiments and report data honestly, regardless of their interests.
After you have reviewed the 6 experiments in the Smoking Bias activity as a class, share these finding with the class. This is real research and clearly shows that bias unfortunately can and does affect scientific research.
The scientific community has long recognized that bias can be found in scientific studies either by unintentional mistakes on the part of scientist or by intentional attempts to make data show a particular, desired result. There are several “rules” or procedures used by the scientific community to eliminate (or at least reduce) bias in science. These procedures include independent duplication and confirmation by others and the requirement for publication in a peer-reviewed journal.
What measures does the scientific community take to minimize bias in science?
