Revision (content from lecture #7) Flashcards

1
Q

Causal Relationships

A

What events cause other events to occur? E.g. X causes Y
Need sufficient evidence to conclude causality
Alternative explanations
Y causes X
Z causes X and Y
Simply correlation – merely a relationship between X and Y
Correlation does not imply causation
Experimental design

Goal
Figure out why something happened or how it came about
Why
Predict what will happen in the future
Form the basis of our decisions
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
2
Q

Three conditions for causality

A

To show one event causes another to occur (i.e., X causes Y) 3 conditions must be met

  • X and Y must be correlated
  • X must precede Y in time
  • All other factors (Z) must be ruled out
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
3
Q

Questionable cause for relationships

A

A causal relationship for which no real evidence exists

→ superstition

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
4
Q

X must precede Y in time

A

Assuming that because two things occurred close in time to one another, the first event caused the second
Eg. The rooster crowed and the sun came up. Therefore the rooster made the sun come up.
Directionality problem
Does X cause Y or does Y cause X?
E.g. does self esteem determine academic achievement or vice versa

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
5
Q

Third variable problem

A

Does an outside or third factor (Z) cause both X and Y?
E.g., Intelligence causes self-esteem and academic achievement?
Can you eliminate all “third” variables?

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
6
Q

Selection Bias

A

Participant variables

  • Biological, behavioural, psychological characteristics
  • -> E.g., personality traits

Environmental variables
–> E.g., place of residence

Selection bias occurs when participant variables leads to selection of a particular environment
- Increases chance of finding a spurious correlation between participant variables and environmental variables

Problem: self-selection in clinical trials
- Need random sampling and random assignment

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
7
Q

Causal Chains

A
  • Causes and effects usually appear as parts of more complex patterns, or a causal chain.
  • Situation in which one thing leads to another, which then leads to another, and so on.
  • Which cause is the real cause?
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Contributory Causes

A
  • A number of causes can also act simultaneously to produce an effect
  • Each cause contributes to the final effect
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

Interactive Causes

A

Causes

  • Rarely operate in isolation
  • Influence (and are influenced by) other factors

Interactive Causes
- Reciprocal influences

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
10
Q

Deductive Reasoning

A

Reasoning from premises (i.e., reasons) known or assumed to be true to a conclusion that follows necessarily from these premises

Deductive reasoning moves down from known general reasons to specific facts
i.e., “top-down” approach

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
11
Q

Inductive Reasoning

A

Reasoning from premises assumed to be true to a conclusion supported (but not logically) by the premises
- Premises provide evidence that makes it more or less likely (but not certain) that the conclusion is true

Moving from specific observations to broader generalizations and theories
i.e., “bottom up” approach

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
12
Q

Empirical Generalisation

A

Drawing conclusions about a target population based on observing a sample population

When generalising from a sample, need to consider:

  • Is the sample known?
  • Is the sample sufficient?
  • Is the sample representative?
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

Reasoning in Psychological research

A

Inductive reasoning
- Draw conclusions about target population from observing sample population
- Construct theories based on observations
== Beware Texas sharpshooter fallacy

Deductive reasoning
- Theories used to make specific predictions (i.e., hypotheses)

Texas Sharpshooter fallacy
- A man in Texas fires random shots at his barn wall, then paints targets around the holes. His neighbours see the barn wall, and are amazed by his accuracy…
→ In Psychology, what could be wrong with doing something like this ?

  • Fitting theories to observations (i.e., painting circles around the holes) is not good science
  • Good science is conducted by first developing a theory and then gathering observations to test the idea
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

Fallacious Reasoning

A
  • Unsound arguments that can appear logical
  • Often persuasive because they appeal to our emotions
  • Often support conclusions we want to believe are accurate
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Fallacies of false generalisation

A

Fallacies of false generalisation:

Hasty generalisation
- Making a general conclusion on the basis of a very small sample

Sweeping generalisation

  • Applying a generally accepted conclusion incorrectly in a specific instance
  • A glass of wine a night is good for your health

False dilemma

  • Forced to choose between two extreme examples without being able to consider additional options
  • -> Either/or, black-or-white fallacy
How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

Fallacies of Relevance

A

Arguments that rely on factors that have little or nothing to do with the argument being made
Appeal to authority

Appeal to tradition:
Ancient wisdom or “mama says…”

Bandwagon:
An uncritical acceptance of others opinions

Appeal to pity:
Conclusion based on feeling sorry

Appeal to fear:
Conclusion based on feeling afraid

Appeal to flattery:
Conclusion based on vanity

Special pleading:
Attempts to make a special exception, without sound justification
We tend to see the world through our own lenses, tilted toward our individual interests

Appeal to ignorance:
Unless something has been proved to be false, it must be true
Often involves shifting the burden of proof
i.e., Claimant asks opponent to disprove conclusion

Begging the question:
The premise of the argument also includes the claim that the conclusion is true
i.e., Circular reasoning

Conclusion: My new diagnostic test for depression is valid and reliable
Premise: Validity and reliability can be established

Straw man:
Exaggerate or distort the opposite opinion, therefore making it easier to attack or discredit
Person A: We should relax the laws on marijuana
Person B: No, any society with unrestricted access to drugs loses its work ethic and goes only for immediate gratification

Red herring:
Introducing an irrelevant topic in order to divert attention away from the original issue

Appeal to personal attack:
Attack the person, not their argument (ad hominem)

Two wrongs make a right:
Attempt to justify a morally questionable action by arguing that it is a response to another wrong action
Actions are independent of each other and each must be evaluated on its own merits

“Capital punishment is fine, since those the government kills don’t have any qualms about killing others”