1. Decide whether the following statements are true or false.
What is Science?
Decide whether the following statements are true or false.

2. What is Science? or True Falseor
True
False
Science is concerned with understanding how nature and the physical world work.
Science can prove anything, solve any problem, or answer any question.
Any study done carefully and based on observation is scientific.
Science can be done poorly.
Anything done scientifically can be relied upon to be accurate and reliable.
 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.

3. What is Science? or
True
False
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.
True
Science is a process by which we try to understand how the natural and physical world works and how it came to be that way.
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.

5. Science actually attempts to disprove ideas (hypotheses).
2. Science can prove anything, solve any problem or answer any question.
False
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.
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.
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.

6. 3. Any study done carefully and based on observation is scientific.
False
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
Any study done carefully and based on observation is scientific.
FALSE.
Science must follow certain rules; otherwise, it'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

7. 4. Science can be done poorly.
True
5. Anything done scientifically can be relied upon to be accurate and reliable.
False
Science can be done poorly, just like any other human endeavor.
Quality control mechanisms in science increase the reliability of its product.
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.

8. 6. Different scientists may get different solutions to the same problem.
Yes No
True
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.
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'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 "prove" their favorite cause, even if the rules of science were not followed. Such causes are properly labeled "pseudosciences". 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.

9. Technological advances Public health issues
7. Knowledge of what science is, what it can and cannot do, and how it works, is important for all people.
True
People need to be able to evaluate scientific information in order to make informed decisions about:
Health care
Environmental issues
Technological advances
Public health issues
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.

10. 8. A hypothesis becomes a theory which becomes a law.
False
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. 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)

12. 9. A hypothesis is an educated guess.
False
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.

13. 10. A general and universal scientific method exists.
False
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.

14. 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 NOT? Science ≠ Proof Science ≠ Certainty
Science ≠ Belief

16. 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.

17. Why is science so useful?
The limitations are the strengths of science.
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

18. What is good science? 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.
Given that science can be poorly done, what is good science?

19. Bias = A prejudiced presentation of material
Two main types of bias:
1. Sampling bias
2. Measurement Bias

20. 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.

21. Factors that contribute to sampling bias
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 such as location, age, gender, ethnicity, nationality and living environment can affect the data gathered.
How to minimize sample selection bias:
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?
Use a RANDOM SAMPLE = every individual has an equal likelihood of being chosen.
Limit the question asked to the specific group sampled.

22. 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
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?

23. Summary
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

24. 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.
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 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?

25. Identifying good science: Look for signs of bias!
Language
Appropriate data reported to back conclusions
Data source
 What are some clues that scientific information you are reading is biased?

26. THE DATA SHOULD CONVINCE YOU,
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!
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”

27. 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?
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.

28. Data Sources University Research Corporate Research
Government Research
Research by Special Interest Groups
All organizations 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.
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.

29. 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
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.
Barnes, Deborah E Why review articles on the health effects of passive smoking reach different conclusions. JAMA. 279(19):

30. You are now 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