Research Methods in Science

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Research Methods in Science

• UC LEADSSummer 2003Lecture 1

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Research Methods in Science Outline of talk

• Overview of general principles of the scientific
  method
• Philosophy of science
• examine objections
• Bayesian and frequentist approach
• Humanistic side of science
• Ethics in science (case studies)
• Scientific writing

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What do you think the scientific method is?
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Elementary Scientific Method

• Hypothesis formation
• Hypothesis testing
• Deductive and inductive logic
• Controlled experiments, replication, and
  repeatability
• Interaction between data and theory
• Limits to sciences domain

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The Scientific Method (mission statement)

• The scientific method is the process by which
  scientists, collectively and over time, endeavor
  to construct an accurate (that is, reliable,
  consistent and non-arbitrary) representation of
  the world

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General principles that pervade all of the
sciences

• Hypothesis generation and testing
• Deductive and inductive logic
• Parsimony
• Sciences presuppositions, domains, and limits

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Hypothesis generation and testing

• Formulation of a hypothesis to explain a
  phenomena
• Educated guess
• A hypothesis must be falsifiable

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A hypothesis must be falsifiable

• The Loch Ness Monster is alive and well
• The Loch Ness Monster does not exist
• There is life on Mars
• There is no life on Mars
• DNA is the genetic material of all life
• DNA is not the genetic material

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Hypothesis Generation and Testing

• Based on my (or someone elses) observations, I
  predict that
• H0 no differences
• HA significant difference

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Lets do an Experimental Test!!
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Experimental Tests What are the main features?

• Clear hypothesis
• Identify independent and dependent variables
• Assign controls
• Repeatable, hence verifiable results
• Used to support or refute claims

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General principles that pervade all of the
sciences

• Hypothesis generation and testing
• Deductive and inductive logic

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Deductive and Inductive Logic (distinction 1)

• The conclusion of a deductive argument is already
  contained implicitly in its premises
• The conclusion of an inductive argument goes
  beyond the information in its premises

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Deductive and Inductive Logic (distinction 2)

• Given the truth of all of its premises, the truth
  of an inductive arguments conclusion follows
  with at most high probability
• Deduction argues from a given models general
  principles to specific cases of expected data

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Deductive and Inductive Logic (distinction 3)

• Deduction argues from a given models general
  principles to specific cases of expected data
• Induction argues in the opposite direction, from
  actual data to an inferred model

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Deductive and Inductive Logic

• One is based on statistics (inductive)
• The other is based on probability

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Deductive and Inductive Logic(telling the
difference)

• Given A fair coin is one that gives tails with
  probability 0.5 and head 0.5 .
• Problem 1 Given that a coin is a fair coin. What
  is the probability that the coin will produce 45
  heads and 55 tails?
• Problem 2 Given that 100 tosses of a coin
  produce 45 heads and 55 tails. What is the
  probability that the coin is a fair coin?

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Why is induction so pervasive and critical in
science?

• Science is almost entirely about unobservables --
  about things and times outside the database of
  actual observations.
• Iron melts at 1,535C (but everywhere?)
• Water boils at 100C (but everywhere?)

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The basis of induction Aristotle

• Aristotle (384-322 BC) offered 3 methods of
  induction
• Unifying concept in deductive arguments, which
  are composed of premises, inductive arguments are
  the scaffolds that raise the status of the
  deductive argument to a law-like status

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The basis of induction Aristotle

• Dialectical induction (Topics). Not entirely
  relevant to scientific research, but useful
• mentor to pupil discourse
• If a skilled pilot is the best pilot and the
  skilled charioteer is the best charioteer, then,
  in general, the skilled person is the best
  person in any particular sphere (Perez-Ramos
  1988)

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The basis of induction Aristotle

• Enumerative induction (Prior Analytics).
  Statements about individual objects provide the
  basis or premises for a general conclusion
• from observing numerous adult humans, an
  inductive argument could conclude that all humans
  have 32 teeth

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The basis of induction Aristotle

• Intuitive induction (Posterior Analytics).
  Direct intuition of the general principles
  exemplified in the data
• bright side of the mood always faces the sun, so
  the moon shines because of reflected sunlight

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General principles that pervade all of the
sciences

• Hypothesis generation and testing
• Deductive and inductive logic
• Parsimony

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Parsimony

• Shortest path or the less complex explanation
  to the true state of nature

A
B
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Parsimony

• Keynes (1962) expressed parsimony as the law of
  the limited variety in nature
• Iron melts at 1,535C
• unlimited natureunique atomsunique
  propertiesno iron, oxygen, no humans (sum of the
  parts)
• 100 chemical elements
• related presuppositions of induction

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Parsimony

• The principle of parsimony recommends that from
  among theories fitting the data equally well,
  scientists choose the simplest theory.
• Thus, the fit of the data is not the only
  criterion bearing on the theory choice

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Parsimony

• Additional criteria includes
• predictive accuracy
• explanatory power
• testability
• fruitfulness in generating new insights and
  knowledge coherent with other scientific and
  philosophical beliefs
• repeatability of results

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Parsimony

• Q Why is parsimony an important principle in
  science?
  .
• A1 The entire scientific enterprise has never
  produced, and never will produce, a single
  conclusion without invoking parsimony
• A2 Economyfacilitate insight, improve accuracy,
  and increase efficiency

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General principles that pervade all of the
sciences

• Hypothesis generation and testing
• Deductive and inductive logic
• Parsimony
• Sciences presuppositions, domains, and limits

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Sciences presuppositions, domains, and limits

• Set of beliefs that allow a person to validate
  her observations, results, conclusions
  (objectivity of science)
• constancy of the universe
• parsimony
• Acceptance and acknowledgement of the knowable
  and the unknowable

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General principles that pervade all of the
sciences

• Hypothesis generation and testing
• Deductive and inductive logic
• Parsimony
• Sciences presuppositions, domains, and limits

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General principles that pervade all of the
sciences

• Hypothesis generation and testing
• Deductive and inductive logic
• Parsimony
• Sciences presuppositions, domains, and limits

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General principles that pervade all of the
sciences

• Hypothesis generation and testing
• Deductive and inductive logic
• Parsimony
• Sciences presuppositions, domains, and limits

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General principles that pervade all of the
sciences

• There are detractors of the idea that a
  scientific method, upon which we are able to make
  claims about the true state of nature, does not
  exist

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General principles that pervade all of the
sciences

• There are detractors of the idea that a
  scientific method, upon which we are able to make
  claims about the true state of nature, does not
  exist

PhilosophicalScientific
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General principles that pervade all of the
sciences
cannot

• Paul Feyerabend insisted that there are no
  objective standards of rationality, so naturally
  there is no logic or method to scienceanything
  goes in scienceit is no more productive of
  truth than ancient myth-tellers, troubadours and
  court jesters

Philosophical
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General principles that pervade all of the
sciences
cannot

• Thomas Kuhn is critical of what he sees as
  modernist misrepresentation of the nature of
  science
• Modernist definitions of science claim that
  science is objective because it is empirical
  (based only on the data of our senses), rational
  (reasonable, or logically defensible) and that
  its presuppositions are obviously true...

Scientific
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General principles that pervade all of the
sciences
cannot

• Kuhn claims science is a social enterprise and as
  such is also quite subjective. He argues that,
  "every individual choice between competing
  theories depends on a mixture of objective and
  subjective factors."

Scientific
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General principles that pervade all of the
sciences
cannot

• Instead, science occurs in revolutions where old
  ideas are thrown out and new ones accepted.
  Science is therefore capricious, and each
  discipline of science cannot share a set of
  pervading principles

Scientific
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General principles that pervade all of the
sciences
cannot

• These revolutions are called
• PARADIGM SHIFTS

Scientific
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astronomy
chemistry
geology
physics
biology
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astronomy
chemistry
geology
physics
biology
General principles and technologies are distinct
to each scientific discipline
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Thought experiment

• You have been awarded a 500,000 grant and can
  spend it on any type of equipment that is
  relevant to your research.
• Make a list of what you will buy and justify it
  (dont worry about EXACT price values as you
  essentially can afford almost anything!)
• (dont forget about Gregorios research!)

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Thought experiment

• Can you safely say that you will not rely on or
  utilize any of the following principles by using
  your new equipment?
• hypothesis generation and testing
• Deductive and inductive logic
• Parsimony
• Sciences presuppositions, domains, and limits

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you
them
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Pervasive inall sciences
Based on Greekphilosophers many others
Non-negotiablepresuppositionsof
perceptionyou see what Iseeyou feelas I
feel
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The Scientific Method (mission statement)

• The scientific method is the process by which
  scientists, collectively and over time, endeavor
  to construct an accurate (that is, reliable,
  consistent and non-arbitrary) representation of
  the world

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Bayesian and Frequentist Approach to Scientific
Research

• Bayesian Statistics have been developed for a
  variety of purposes, such as designing
  experiments, estimating the values of quantities
  of interest, and testing hypothesis
• Useful because this family of statistics takes
  into account prior results as opposed to
  assigning independence to each result, thereby
  introducing efficiency

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Bayesian and Frequentist Approach to Scientific
Research

• For a loaded dice (biased for 6)
• The frequentist views dice throws as independent
  events, each number or face having an equal
  probability each value has a 1/6 probability of
  appearing.
• The Bayesian, the probability of getting a 6
  will be more than just 1/6 (as will the
  probability of being thrown out on your ear!)

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Bayesian Approach to Scientific Research

• The search for patterns in data will be more
  realistic as you do not discard prior
  knowledge -- it helps you get to the answer
  much faster
• Calculations are not very difficult for small
  sample sizes, but can get complicated for large
  oneslets see an example

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Bayesian Example

• Coin toss determines the configuration of the
  marbles that go into an opaque urn
• heads place 1 white 3 blue marbles(WBBB)
• tails place 3 white 1 marbles blue (WWWB)
• Only coin-tosser knows

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Bayesian Example
Ratio of the likelihood of heads to the
likelihood of tails
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Posterior probability
Number of draws
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Bayesian Approach to Scientific Research

• Your confidence in the results (and hence your
  hypothesis) increases tremendously with each draw
  of a marble
• If trials are expensive then using likelihood
  values are important
• Can be computationally complex (trade off)

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The Humanistic side of Science

• Your perceptions of the humanistic side of
  science
• It can lie between ones research and ones
  beliefs
• It may not be realized at the outset
• It may change during your career
• You may not want them to intermingle

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Science as a Liberal Art

• The search for and the advancement of knowledge
  and truth is a common goal among scientists
• The truth will (hopefully) be used to improve
  the world in which we live in
• The truth will be used for just and moral
  purposes

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Science as a Liberal Art

• As scientist, we may be in dilemmas that will
  challenge out personal beliefs
• A strong conviction in what one believes should
  reflect the kind of work one undertakes
• May or may not reflect current social climate

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Science as a Liberal Art

• Examples of controversial research
• stem cell research
• genetic engineering / GM food
• nuclear sciences
• control systems (used by the defense)
• biological control
• alternative fuel research

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Science as a Liberal Art

• Do you have ethical boundaries that you have
  considered in your work?

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Ethics Case Studies

• Isa and Senait will lead discussion
• Introduce the paper
• Break into groups
• Read and discuss paper
• Develop topics for big discussion
• Introduce second ethics issue (no break-out
  groups)

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Ethics in Research

• Reporting of data accurately is seen not only as
  a high professional quality, but also a moral
  one.
• Why?

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Ethics in Research

• Ethical researchers do not plagiarize or claim
  credit for the results of others
• They do not misrepresent sources or invent
  results
• They do not submit data whose accuracy they have
  reason to question, unless they raise the
  question
• They do not conceal objections that they cannot
  rebut
• They do not caricature or distort opposing views
• They do not destroy or conceal sources and data
  important for those to follow

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Research Ethics and Science Writing Example
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Research Ethics and Science Writing Example
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Research Ethics and Science Writing Example
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Research Ethics and Science Writing Example
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Research Ethics and Science Writing Example
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Research Ethics and Science Writing Example
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Research Ethics and Science Writing Example
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Concept MapWater Example