LU Scientific Method Science and Ethics Questions

What is Science?THE SCIENTIFIC METHOD
SCIENCE & ETHICS
(SECTIONS 1 & 2: CHAP.
1)
What is Science?
 Let’s start with any academic pursuit, the desire to understand the world around us
and have better comprehension of our experiences. There have been multiple ways
of doing this in the past: philosophy, religion, superstition, etc., but the best and
most reliable method has been science.
 Science is a Greek work that roughly translates to “knowledge”, and science
attempts to create understanding of the natural world around us. It does not
attempt to explain anything beyond the natural world, including anything that falls
into the supernatural.
 Science is, quite simply, a way of asking and answering questions. The difference is
that in science a particular set of steps has to be followed in a systematic way,
whereas in everyday life we often skip steps or do them haphazardly.
 Science is as simple as “being curious about Nature” You may ask what is
“Nature”, it is everything around us, from what we can see to what we cannot see.
From the speck of dust on our desk to the expanse of the Universe.
Before There Was Science
 Early man was unaware of how the world around them worked. This led to
much fear when things would happen in nature, mostly because they didn’t
understand what was happening. Not only that, a lack of understanding of
nature led to a much harder and shorter life than what we enjoy now.
 For example, let’s look at lightning. The bright flash, the loud crack of
thunder, the destruction caused by a lightning strike: Early man was
terrified of lightning because they assumed it was some terrible force of the
gods.
 This assumption and fear continued up until the time of Benjamin Franklin.
Through a scientific experiment with a kite in a thunderstorm, he
determined that lightning was nothing more than a large static electric
spark, and NOT a force of the gods.
 Not only did he help us to understand the nature of lightning and electricity,
he took the fear out of thunderstorms by describing it as a natural
occurrence, and subsequently developing a technology to counter the
destructive effects of a lightning strike: the Lightning Rod.
The Lightning Rod was
placed at the highest
point on homes and
buildings in order to
attract a lightning strike.
The static electricity of
the lightning would
contact the metal rod
first and travel down an
attached cable into the
ground. This would
disperse the charge
along the surface of the
Earth, rather than
concentrate it on the top
of a building, possibly
causing damage or fire.
Franklin’s First Lightning Rod
The Value of Science
 Thus, Ben Franklin’s experiment with his kite allowed
us to feel safer in a world where thunderstorms are
relatively common.
 Once we understand how the world around us works
through science, we can live in less fear and use the
information to create technologies that can improve
our lives.
 The greatest questions and problems in our time can
likely be answered through science.
The Language of Science
 Students are often afraid of science because of the language and
terminology. The language of science is rooted in either Greek or Latin,
which few people speak today.
 The timing of the development of science at the beginning of the
Renaissance led to the use of Greek and Latin. In fact, ALL academic work
at the time was written in Latin as it was the universal language used by
scholars in Europe.
 Before the Renaissance, academic work was done almost exclusively by
clergymen. The Roman-Catholic church used Latin as a universal
language to connect all their congregations to the Vatican and the Pope.
Therefore, this was the language used by clergy-associated scholars of the
time and it was used in science to break down language barriers between
nations.
 This helped the collaboration between scientists working on the same
phenomenon.
Science Terminology Breakdown
 Once you understand the root language used, you can see
that scientific terminology isn’t so scary and it often describes
the phenomenon very accurately and with minimal language.
 For example: Photosynthesis is a word that breaks down into
“photo” meaning light, “syn” meaning together, and ”thesis”
meaning to put or putting.
 Photo-syn-thesis = light-together-putting
 This literally translates to ”Putting Things Together by Using
Light”, which accurately describes the process of
photosynthesis.
Science Terminology Breakdown
 Bradykinesia
 Brady=slow, kin=movement, -esia=condition
 This simply means having a condition of slow reflexes.
 Costochondritis
 Costo=ribs, chondr=cartilage, -itis=inflammation
 This simply means having pain in the cartilage of the ribcage
 Choledocholithiasis
 Chole=bile, doch=duct, lith=stone, -iasis=abnormal condition
 This means having a gall stone blocking the bile duct.
Natural vs. Social Science
 Natural Science is always quantifiable, meaning it can be measured. This
means that any questions that do not have measurable data do NOT fall into
the realm of science.
 Social Sciences are those that use some measurable data, but often rely on
constructs that are concepts created by the human mind in order to navigate
the world through our experiences. These constructs have no empirical
evidence, meaning they are not experienced through the senses, and only exist
in the mind.
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An example of a construct would be intelligence. Intelligence isn’t directly measurable in the natural
world and is inferred through a series of actions or tests.
Happiness would be another construct in the world of psychology that has no quantifiable
measurement or objective reality, and has a unique definition to every individual.
 Being that we are human, we have a bias when studying ourselves that distorts
any data from being purely empirical. This is why the social sciences deal
exclusively with human behavior.
 Examples of social sciences are psychology, economics, sociology, political
science etc.
Systems of Measurement
 Since quantification is such an important part of science,
it’s important to have consistent and accurate systems of
measure.
 The traditional systems of measure were vague and
relied on common objects.
 For example, a chain was an imperial unit of length that
was the distance between two wickets of a cricket pitch,
which was 22 yards. 10 chains made a furlong, 8
furlongs made a mile, and 3 miles made a league.
 There was no consistency in moving from one unit to the
next, which made conversion difficult and mathematical
calculations incredibly cumbersome.
Metric System of Measurement
 In the mid-industrial period, a French government official and
scientist named Antoine Lavoisier gave us a way to simplify
the math with his creation: The Metric System.
 Changing units of measure only requires moving a decimal
place, rather than doing a multiplication or division calculation
to convert the numbers properly.
 For example: converting 2 yards to inches requires multiplying
the yards by 3 for conversion to feet, then multiplying it by 12
for inches. 2x3x12=72 inches.
 Move from 1.67 meters to centimeters only requires
movement of the decimal to the right two spots. 1.67 meters =
167 centimeters. Simple, and it reduces calculation errors.
What is the tool of the Scientist?
SIMPLE: The Scientific Method
Observation – I notice that salt water stays liquid at
the same temperature that fresh water freezes.
Step # 2: Question – Does the presence of salt change the
freezing temperature of water?
Step # 3: Testable Hypothesis – Salt dissolved in water
lowers the freezing temperature.
Step # 4: Experimentation – Dissolve salt into water at
increasing ratios and measure the temperature when it freezes.
Step # 5: Results/Analysis of data – As more salt is added
to water, the freezing temperature drops lower.
Step # 6: Conclusion – The addition of salt to water
directly lowers the freezing temperature.
 Step # 1:
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The Scientific Method
An Observation: Science?
The raspberries did not grow well this year!
Why are the raspberries poor this year?
 In this case, the question will have numerous possibilities that need to be
considered:
Not enough water/too much water
•
Not enough sunshine/ too much sunshine
•
Poor nutrients in the soil
•
Damage from insects
•
Contaminated air or water
•
Competition for available resources by neighboring plants
Etc.
•
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At this point we would research to find out what we know about each
of these questions to see if there are possible reasons or factors to
consider one possibility over another. This may lead to us acquiring
the correct explanation more quickly.
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The best way of choosing a question to test scientifically is by using
a classic logical principle used by scientists: Occam’s Razor.
Occam’s Razor
 Occam’s razor, also spelled Ockham’s razor, also
called law of economy or law of parsimony, principle
stated by the Scholastic philosopher William of
Ockham (1285–1347/49) that pluralitas non est ponenda
sine necessitate, “plurality should not be posited without
necessity.”
 The principle gives precedence to simplicity: of two
competing theories, the simpler explanation of an
entity is to be preferred.
 The principle is also expressed as “Entities are not to be
multiplied beyond necessity.” (Encyclopaedia Britannica,
2017)
Formulate a Hypothesis
 The Hypothesis takes your thoughts and questions and
transforms them into a specific statement that can be
tested for plausibility. A Hypothesis is always an
educated guess about the most likely answer to the
question.
 A hypothesis is never in the form of a question. It is
always a predictive statement of fact or “cause and
effect” between the two main variables in the experiment.
This is a statement that is specific, testable, and
falsifiable.
 In our case, if we wanted to test whether there was too
much or not enough water, we might use this as our
hypothesis:

The raspberries did not grow well because the plants did not
receive enough water to grow many large berries.
Good vs. Bad Hypotheses
Examples of BAD hypotheses
Examples of GOOD hypotheses
• Plants will grow better when given
Miracle Grow
• Plants will grow taller when given
Miracle Grow
• Girls are smarter than boys
• Girls will score higher on math tests
than boys
• Hermit crabs choose colorful shells
more often than drab shells
• Hermit crabs like colorful shells
 All of the above hypotheses use
language that is ambiguous and
not measurable. That means that
no empirical evidence can be
obtained and therefore the
hypothesis isn’t testable or
falsifiable.
 These hypotheses have taken
the ambiguous red words on the
left and used quantifiable words
or concepts to make the
statements testable and
falsifiable.
Formulate an Experiment
 Define your variables: For our example hypothesis, we
would need to define what “many” and “large” mean so we
can clearly interpret the results. It might require us to use
other year’s yields of berries for comparison since we noticed
the yield was poor in this season.
 We then create an experiment to test how changing our
“manipulated” or independent variable will affect our
dependent variable.
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The independent variable is what you intentionally change during the
experiment. The dependent variable produces your measurable results,
thus it always “depends” on the independent variable.
Or another way to remember is the phrase “I intentionally change the
independent variable.”
 *It is important to maintain all other variables constants as
much as possible. The more other variables are consistent
throughout the experiment, the more closely an association
can be made between the two variables being tested.
Example Experiment
 Several raspberry plants will be placed in the same
moderately lit environment with the same air and soil
composition with careful management and removal
of any pest insects.
 Each plant will receive a different amount of water at
the same time intervals.
 Once the plants begin to produce berries, the
number and size of berries will be recorded using
calipers.

In this case, the calipers are the technology we use to record
our results.
The Calipers are a tool
developed to perform a
task more effectively.
Technologies are
developed by advances
in science. In this case,
we need advances in
the system of
measurement (metric),
the methods of metal
production (metallurgy),
understanding of
electricity, digital
precision (computing)
etc. etc. etc.
The tools of science are
developed from
numerous advances in
science.
We Use Technology to Measure
Objectively, Giving us Empirical
Evidence
Results/Analysis of Data
 Often, analysis of data requires statistical analysis by
an expert to determine whether the results are
“statistically significant”.

This just means that they analyze to make sure the differences
recorded can’t be attributed to random chance but are due to a
real “cause and effect” relationship.
 Often, the more data points available, the less likely
the results are due to random chance. Therefore
larger studies are almost always better than small
studies.
More Data
Points Are
Better
In the case where you
have minimal data, be
careful not to make too
many assumptions with
limited results. The
results can indicate a
trend, or it could be an
anomaly that may not
continue in the same
pattern.
Results/Analysis of Data
 We gathered the raw data by measuring 1000 berries
from the different plants with different growing conditions.
 We average the size of the berries, compare different
growing conditions against each other, and use statistical
analysis to be sure it isn’t due to random chance.
 After analyzing our results of our experiment we find no
appreciable difference between the number of berries or
the size of berries regardless of the amount of water
received.
 The hypothesis is not supported by the data, so we reject
the hypothesis.
My Hypothesis Was Wrong!
Conclusion and Re-testing
Our hypothesis was wrong. The amount of water does not seem to be
affecting the the raspberry yield. Upon further observation, we are noticing
poor yields where there are beetles present. This is a possible alternative
explanation.
One Important Note
 Science never “proves” anything, even though we
like to think of clear and undeniable results that
confirm a hypothesis to be proof.
 Rather, if the results clearly indicate that the
hypothesis cannot be DIS-proven, then we have to
accept the hypothesis as the most likely explanation
to the question we asked.
 It still leaves the possibility open in the future for
someone else to DIS-prove the hypothesis with retesting or a different experiment that produces
contradictory evidence.
I have to start over again!
 Partially right, my answer to the question “why are the raspberry
yields poor?” may not have been right and if that is the case I must
offer another educated guess (hypothesis) to explain this
observation. It would be wise to use the next simplest explanation
using Occam’s Razor.
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Beetles?
Soil composition?
Other plants competing for resources?
 Any or all of these potential answers require me to go back to Step #
3 and proceed once again through the “Scientific Method”
 The scientific method can “prove” or “disprove” any hypothesis
tested.
 For a scientist seeking answers to questions about Nature this
process will be repeated over and over again until a reproducible,
consistent and verifiable conclusion is reached.
 In this way, science is an Iterative Process, meaning that the cycle
of hypothesis and experimentation is repeated, likely without end.
Is “Theory” fact or is it just “Theory”?
 These terms are defined differently in science than in everyday speech.
 For science “Theory” is the best possible explanation for an observation
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about Nature.
If a new and more valid explanation for an event in Nature is
offered and accepted by the majority of scientific experts in the
field, the previous “Theory” is replaced with the new and improved
“Theory”.
Remember a “Hypothesis” is an educated guess about a specific cause
and effect relationship, whereas a “Theory” is the best acceptable
explanation at the moment to explain an event in Nature.
A combination of accepted hypotheses are used to make the larger
theories.
Theories often explain large natural phenomenon and they are also
falsifiable, or can be disproven, just like their constituent hypotheses.
Experiments usually test smaller portions of a theory, thus supporting
the theory at large. When data contradicts a theory, it can be amended
or altered.
When enough contradicting evidence exists, the theory is replaced with
a better explanation.
Scientific Laws
 Laws are a bit more reliable and established than
theories. Laws use repetitive observations of nature
to construct a law that can be used to not only
explain some aspect of nature, but reliably predict
the future.
 These laws are often mathematical relationships and
can be used to calculate expected future events.
 For example, Newton’s Second Law of motion is
defined as F=ma, or the force is equal to the mass of
the object multiplied by the acceleration it
experiences (more on this later).
Experiment, Theory, and Law
 For example, gravity has a larger theory that explains it
how it works (Einstein’s theory of a time/space vortex), a
law that defines how gravity acts (Newton’s mathematical
formula), and individual experiments that test specific
parts of these two.
 A specific experiment might be to measure the
displacement, speed, and acceleration of a falling object
in a vacuum.
 The data from the experiment can be used to verify the
law of gravity mathematically.
 If the experiment does NOT falsify the theory at large,
then the evidence from that experiment further adds to
the pool of information used during inductive reasoning.
Scientific Method and Theory Formulation
Pseudoscience
 Pseudoscience is “false science”, when reviewed
by peers the science cannot be reproduced nor
validated with evidence.
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Pseudoscience uses the tools and technology of science
Does NOT use the scientific method
Results are not repeatable
Evidence is lacking
Often used to explain difficult to understand phenomena
 E.g. Cryptozoology (bigfoot, aliens, loch ness
monster), Conversion Therapy, Eugenics, Astrology,
Psychics: ESP/clairvoyance/channeling etc.
Common Traits of Pseudoscience
 According to Schmaltz and Lilienfeld, there are 7 clear
signs that show something to be pseudoscientific:
 1. The use of psychobabble – words that sound scientific
and professional but are used incorrectly, or in a
misleading manner.

Common in “pop” psychology, i.e. Primal Scream Therapy.
 2. A substantial reliance on anecdotal evidence.
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Single data point
False attribution of cause
 3. Extraordinary claims in the absence of extraordinary
evidence.
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Chiropractic can cure cancer
Common Traits of Pseudoscience
 4. Claims which cannot be proven false.
 John: “I believe that psychic powers exist”
 Jane: “Where’s your proof?’
 John: “Nobody has proven that psychic powers DON’T exist.”

*This is tricky, because John doesn’t provide any evidence to support his claim, but
relies on the fact that completely disproving something that exists in someone’s
mind is nearly impossible to do with current technology. This goes against the
requirement that a hypothesis be testable and falsifiable. This means that the claim
is based on faith and not science, hence, pseudoscience.
 5. Claims that counter established scientific fact.
 I.e. the world is flat, the Earth is only 6,000 years old.
 6. Absence of adequate peer review.
 Very important in the process of publishing material. A lack of peer review means
the information hasn’t been vetted yet.
 7. Claims that rely on confirmation rather than refutation.
 E.g. anti-vaccine movement.
Why is this important?
 Students should NEVER walk out of college not
knowing the difference between science and
pseudoscience.
 “There was only a modest decline in
pseudoscientific beliefs following an
undergraduate degree, even for students who
had taken two or three science courses,”
psychologists Rodney Schmaltz and Scott Lilienfeld
said of the results.
Pseudoscience Examples
 Creation science is the belief that the origin of everything in the
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universe is the result of a first cause, brought about by a creator
deity, and that this thesis is supported by geological, biological, and
other scientific evidence.
Astrology: believes that the position of celestial bodies affects human
activity and personality.
Phrenology: believes that human personality traits can be determined
by the shape and location of bumps on the head.
Channeling/ESP: Often uses a psychological technique called “Cold
Reading”, in which general information provided by the “psychic” is
given meaning by the person receiving the reading.
Vitalism: This branch of chiropractic philosophy believes in “innate
intelligence” as a phenomenon to explain the body’s ability to heal
naturally in the absence of interference. The main principle is used to
justify using chiropractic to treat unrelated disease states like
diabetes and cancer.
Cold Reading
 Cold Reading is a method that relies on receptive clients. One has to be
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willing to believe for it to work.
Cold reading begins by applying Barnum Statements: A statement of fact
about us that seems personal, but is in fact a universal experience of all
humans. This gains the client’s trust.
Then the reader will make a series of vague predictions that can be easily
backtracked or the meaning of the prediction can be changed. The subtle
verbal and non-verbal reactions of the client guide the reader in
determining how close they are to a true statement.
This process continues until the client reveals the details of the prediction
once the reader is close enough.
This can be done for monetary gain, like a confidence scheme. What’s
important to understand is that fortune tellers and cold readers are not
science. They could be perceived as pseudoscience should someone truly
believe in their powers, but it is easily explained once you know the
process of cold reading.
Inductive versus Deductive Reasoning
 Deductive reasoning, also deductive logic or logical deduction
or, informally, “top-down” logic, is the process of reasoning
from one or more general statements (premises) to reach a
logically certain conclusion.
 Deductive reasoning (top-down logic) contrasts with inductive
reasoning (bottom-up logic) in the following way:

In deductive reasoning, a conclusion is reached reductively by applying
general rules that hold over the entirety of a closed domain of discourse,
narrowing the range under consideration until only the conclusion is left.
 In inductive reasoning, the conclusion is reached by generalizing or
extrapolating from a single point of initial information to produce a generalized
explanation.
An Example of a Deductive Argument
All men are mortal.
Albert Einstein was a man.
Therefore, Albert Einstein was mortal.
 The first premise states that all objects classified as “men” have
the attribute “mortal”.
 The second premise states that “Albert Einstein” is classified as a
“man” – a member of the set “men”.
 The conclusion then states that “Albert Einstein” must be
“mortal” because he inherits this attribute from his classification
as a “man”.
 In deduction, it the premises are true, and the argument is
logically sound, then the conclusion MUST be true and
CANNOT be false.
Example of an Inductive argument
 Inductive arguments are based on individual observations of a phenomenon and
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are often predictive. Inductive reasoning is used to make scientific laws.
Unlike deductive arguments, inductive reasoning allows for the possibility
that the conclusion is false, even if all of the premises are true. Instead of
being valid or invalid, inductive arguments are either strong or weak, which
describes how probable it is that the conclusion is true.
A classical example of an inductive argument:
All of the swans we have seen are white.
Therefore, it is likely that all swans are white.
This example allows for the possibility that the conclusion is false. The key
word used is “likely”, which is not an absolute statement, but is based on the
strength of the evidence. There could be a point in the future in which the
observation of a black swan will falsify the conclusion of the inductive
argument.
E.g. Every autumn there are hurricanes in the tropics.
Therefore, it is highly likely that there will be a hurricane in the tropics
sometime this autumn.
Inductive vs. Deductive
Chapter 1.2
SCIENCE AND ETHICS
Ethics & Science
 It is the study of right and wrong in human endeavors. At a more
fundamental level, it is the method by which we categorize our values
and pursue them. Do we pursue our own happiness, or do we sacrifice
ourselves to a greater cause?
 Ethics is a requirement for human life. It is our means of deciding a
course of action when the way is unclear.
 A proper foundation of ethics requires a standard of value to which all
goals and actions can be compared.
 Ethics: includes terms such as: Right vs. Wrong
Honesty
Respect of one’s Human Rights
Moral Beliefs and Conduct
Ethics & Science
 In science, several principles are held in high moral regard:
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Honesty: Truthfulness is the essential pursuit of science
Universality: Regardless of religion, culture, language, creed, the same result is
found.
Communal: Knowledge must be shared amongst others. Mutual respect for
scientists is essential. Peer review and publication.
Indifference: Work must be objective, regardless of the desired outcome.
Humility is also essential to saying “I was wrong” when things don’t work.
Organized Curiosity: The will of authority does not hold sway over one’s
acceptance.
 Science should always be questioned, but it should never be
corrupted for personal gain.
Science & Ethics
 Since ethics is incorporated into science, many of the questions we
have about nature also include whether or not the science we practice
is ethical or not. In some cases it can vary from person to person and
topic to topic.
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Most ethical dilemmas address the effect of science on living things.
e.g. ethics of nuclear physics
e.g. ethics of genetic manipulation
e.g. ethics of the removal of life support/assisted suicide
e.g. ethics of animal experimentation
e.g. ethics of stem cell research
 All of these examples present moral dilemmas to people who are
involved in these issues and as such must be evaluated for their
contribution to human society vs. the impact on rights, freedoms, and
even legal arguments in some cases.
Case Study: Andrew Wakefield
 Dr. Wakefield published a paper that proposed a link between the MMR
(measles-mumps-rubella) vaccine and autism that.
 The publisher (The Lancet) retracted the publication years later following a
revelation that Wakefield’s research was sponsored by an anti-vaccine
group attempting to sue vaccine manufacturers. He also had financial gain
at stake as he was in the process of producing an alternate therapy to
boost the immune system of children.
 It was also found that Wakefield fabricated some of his results in order to
create a stronger connection between autism and the vaccine.
 He lost his job at a prestigious hospital and lost his medical license after an
ethics committee determined he had violated ethical standards.
 The final straw: Wakefield refused to reproduce his results after several
others tried to replicate a similar finding and could not. This goes back to a
“reproducible, consistent, and verifiable conclusion” being essential.
The Fallout
 The effect of Wakefield’s ethical compromise is far
reaching:
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Measles was all but eradicated in the United States, but is now
having regular cases of breakthrough disease due to a lack of
vaccination.
Vaccinations throughout the western world are largely down
Measles, a deadly disease to children in underdeveloped nations, is
present in global populations where it shouldn’t be.
Easy and frequent international travel in the modern world means
quick transmission of diseases between distant populations.
https://www.newsweek.com/2015/02/20/andrew-wakefield-father-antivaccine-movement-sticks-his-story-305836.html
Chapter 1 review quiz
Started: Sep 23 at 7:43pm
Quiz Instructions
Following the lecture on chapter 1, please complete the following 10 question quiz for points.
You will be given 3 attempts to complete the quiz and I will take the highest grade, so don’t worry if you get it
wrong on your first attempt. Pay attention to the explanation of why your answer was wrong in order to get
the answer correct on your second attempt. You have 30 minutes to complete each attempt at the quiz,
which is more than enough time.
Question 1
10 pts
A hypothesis is never in the form of a question.
True
False
Question 2
10 pts
What is the one major difference between the natural sciences and the social sciences?
The social sciences NEVER use quantitative data
Social sciences never test a hypothesis.
Neither uses experiments to form larger theories.
The natural sciences NEVER use qualitative data
Question 3
10 pts
A hypothesis is formed as an EDUCATED guess. Which of the following would help us in
that process?
Superstition
Random guessing
Intuition
Research and deductive logic
Question 4
10 pts
A scientific theory is an explanation of observed phenomena without experimental
evidence.
True
False
Question 5
10 pts
The ____________ always responds as a result of changes made to the independent
variable.
Theory
Dependent Variable
Conclusion
Hypothesis
Question 6
10 pts
When is it determined that science has fully confirmed a hypothesis to be valid?
When the hypothesis has a conclusion that is consistent, reproducible, and verifiable
When data from one experiment supports it
When the conclusion involves supernatural explanations.
When the hypothesis produces a technology.
Question 7
10 pts
Inductive logic makes general statements, that when combined with each other eliminate
possibilities, and leads to a conclusion that MUST be true.
True
False
Question 8
10 pts
Which of the following is NOT one of the ethical principles held in high regard among
scientists?
Universality
Communality
Honesty
Justice
Indifference
Question 9
10 pts
Which of the following would be a red flag that may indicate something is
pseudoscience?
Claims which can be falsified.
Experiments that produce repeatable data.
Accurate use of technical terminology
Claims that rely on anecdotal evidence
Question 10
10 pts
A theory is an explanation of a topic that fits most or all of the observed experimental
data; whereas a law is something that has been observed consistently and without
variation through countless experiments.
True
False
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