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Summary Exam 1 Scientific and Statistical Reasoning UvA Year 2
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Summary of Scientific and Statistical Reasoning Exam 1
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W1.1CHAPTER 1 (BOWELL AND KEMP) – INTRODUCING ARGUMENTS
Good habits as a thinker:
- Open-mindedness: The willingness to revise and abandon our beliefs if they are shown
to be faulty
- Intellectual courage: The willingness to engage in argument and to open one’s own
beliefs and reasoning up to analysis
- Intellectual autonomy: The willingness to go against the tide of popular and widely
held opinions, or to adopt unpopular ones if there are good reasons to do so
Persuasion attempt: Takes place when a person makes an effort to influence another person to
change their beliefs
1. Argument: A statement that is supported by other statements to bring about a point of
view or to recommend an action – An attempt to persuade by giving good reasons (=
an explanation for an event) for thinking that some claim is true (= to say that a claim
is true is to say that what is claimed is how things actually are) – ‘Why?’
- Justification: The action of showing something to be right or reasonable
- Conclusion: The primary claim; the one we are trying to get others to accept
- Premise(s): Any claim put forward as support for the conclusion of an
argument, however certain or uncertain that claim may be
- Unsupported claim: A single claim of which the arguer hopes to convince their
audience, without at least one premise
2. Rhetoric: Any verbal or written attempt to persuade someone to believe, desire or do
something that tends to rely on the persuasive power of certain words and verbal
techniques to influence beliefs, desires and actions just by appealing to desires, fears
and other feelings – Can be manipulative and coercive
Proposition: The factual content expressed by a declarative sentence on a particular occasion
– The same proposition may be expressed by different sentences (E.g.: ‘Her name is Sheila’
expresses the same proposition as ‘She is called Sheila’) – Indexical: A linguistic expression
whose reference can shift from context to context (E.g.: the indexical ‘you’ may refer to one
person in one context and to another person in another context)
When analysing attempts to persuade, we have to perform three tasks:
1. Distinguishing whether an argument is being presented
2. Reconstructing the argument so as to express it clearly, and so as to demonstrate
clearly the steps and form of the argument’s reasoning
- Standard form: Provides us with the most comprehensive and clearest view of
an argument
- Inference bar: The line between premises and conclusion is called an
inference bar – Can be read as standing for ‘therefore’
- Argument-reconstruction: The argument set out in standard form
3. Evaluating the argument, asking what is good about it and what is bad about it
1
,The identification of conclusions:
- Trying to see what the main point of the text or speech is
- Extended arguments: When one argues for one point, then a second, and then uses
those conclusions as premises in an argument for a third and final conclusion –
Intermediate conclusion: Conclusion that is used as a premise for a further argument
- Conclusion indicators: Words that indicate that a writer or speaker is putting forward
an argument (E.g.: ‘therefore’, ‘hence’, ‘implies’, ‘since’ etc.)
- Explicit conclusions: When a writer or speaker expresses their conclusion directly and
more or less clearly ≠ Implicit conclusions: Conclusions that remain unexpressed
The identification of premises:
- Trying to understand the writer or speaker’s reasons for believing their conclusion
- Premise indicators: Words that indicate that a writer or speaker is putting forward a
reason (E.g.: ‘my reason is’, ‘my evidence for this is’, ‘because’, etc.)
- Implicit premises: Premises that remain unexpressed
Explanation: When a relation of cause and effect is emphasised between one event and
another – Attempts to illustrate why something is the case, not that something is the case →
Easily confused with an argument!
CHAPTER 1 (HALPERN) – THINKING: AN INTRODUCTION
Twin abilities:
1. Knowing how to learn
2. Knowing how to think clearly about rapidly proliferating information
Thinking and communicating are inextricably related – No one can communicate clearly if
their thinking is muddy
‘Thought and knowledge are power’ → Knowledge is powerful only when it is applied
appropriately, and thought is powerful only when it can utilise a large and accurate base of
knowledge
Knowledge: A state of understanding that exists only in the mind of the individual knower
Critical thinking: The use of those cognitive skills or strategies that increase the probability of
a desirable outcome – Thinking that is purposeful, reasoned and goal-directed – Involved in
solving problems, formulating inferences, calculating likelihoods and making decisions –
When the thinker is using skills that are thoughtful and effective for the particular context and
type of thinking task
- Critical: Denotes an evaluation component
Non-directed/automatic thinking: Thinking that underlies routine, dreaming, the rote recall of
information etc.
2
,Cognitive process instruction: Area of psychology where the goal is to utilise the knowledge
we have accumulated about human thinking processes and mechanisms in ways that can help
people improve how they think
Critical thinking instruction model:
1. Explicitly learning the skills of critical thinking (E.g.: recognising semantic slanting,
seeking out contradictory evidence, using metacognition that allows beginners to
monitor performance and to decide when additional help is needed, making risk-
benefit assessments etc.)
- Based on two assumptions:
1. There are identifiable and definable thinking skills that students can be
taught to recognise and apply appropriately
2. If recognised and applied, the students will be more effective thinkers
2. Developing a disposition for effortful thinking and learning – Being motivated and
willing to exert the conscious effort needed
- Willingness to plan (= prescriptive descriptions about what to do and the
prevent habitual responses that may not work) – Learning to check impulsivity
and plot responses – Self-regulation!
- Flexibility: Willingness to bear new ideas in mind and reconsider old problems
- Persistence: Willingness and ability to keep at a task
- Willingness to self-correct and admit errors – Self-justification: Making
excuses for a belief or behaviour
- Mindfulness: Drawing novel distinctions – Opposite of the ‘automatic pilot’
- Consensus-seeking: An openness in thinking that allows members of a group
to agree on some aspects of a solution and disagree on others – Allows
individuals to accept what is good or true about an alternative position – Does
not mean caving in to majority opinion or forcing others to agree with you!
3. Directing learning activities in ways that increase the probability of trans-contextual
transfer (E.g.: drawing a diagram that organises the information, listing additional
information before answering a question, categorising findings etc.)
4. Metacognitive monitoring
LECTURE W1.1
Critical thinking = Attitude + Knowledge + Thinking skills
Argumentative theory of reason: Suggests that the main function of reasoning is to exchange
arguments with others – Predicts that reasoners are biased and lazy when they produce
arguments, but are objective and demanding when they evaluate others’ arguments
3
, W1.2
CHAPTER 1 (FIELD) – WHY IS MY EVIL LECTURER FORCING ME TO LEARN
STATISTICS?
Quantitative research: Deals with numbers, logic and an
objective stance
Qualitative research: Generalising and testing theories
by analysing language (such as conversations, magazine
articles and media broadcasts)
THE RESEARCH PROCESS
Research process:
1. Observation
2. Theory: A set of principles that explains a
general broad phenomenon – Well-established
3. Hypothesis: A proposed explanation for a
narrow phenomenon or set of observations – An informed, theory-driven attempt to
explain what has been observed – Untested
4. Prediction: Emerges from a hypothesis and transforms it from something unobservable
into something that is
5. Collecting data
- Independent variable/predictor variable: A variable thought to be the cause of
some effect – Manipulated variable
- Dependent variable/outcome variable: A variable thought to be affected by
changes in an independent variable
- Level of measurement: The relationship between what is being measured and
the numbers that represent what is being measured
- Categorical variable: Made up of categories – Distinct entities
- Binary variable: Made up of two distinct categories (E.g.: ‘yes’ or ‘no’)
- Nominal variable: When two things are equivalent in some sense
without a specific order or ranking (E.g.: hair colour) – The only way
that nominal data can be used is to consider frequencies
- Ordinal variable: When categories tell us not only that things have
occurred, but also the order in which they occurred – Does not tell us
about the differences between points on a scale (E.g.: education level)
- Continuous variable: Gives us a score for each person and can take on any
value on the measurement scale that we are using
- Interval variable: When equal intervals on the scale represent equal
differences in the property being measured (E.g.: temperature)
- Ratio variable: Goes a step further than interval data by requiring that
in addition to the measurement scale meeting the requirements of an
interval variable, the ratios of values along the scale should be
meaningful – True and meaningful zero (E.g.: income)
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