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PSYC0 104 > Chapter 2: Psychological Methods > Flashcards

Chapter 2: Psychological Methods Flashcards

1
Q

What should you consider when studying humans?

A

Complexity, Variability, Reactivity

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2
Q

Humans have 500 neurons in the brain (consideration).

A

Complexity

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3
Q

Every person is different (consideration).

A

Variability

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4
Q

Reactions differ when observed vs. not observed (consideration).

A

Reactivity

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5
Q

A stand-in for humans that will be simpler (eg. flatworms that have 500 neurons or lab rats)

A

Model Species

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6
Q

Other sources for people’s beliefs (limited):

A

Experience (Subjective), Intuition (Common Sense), An Authority (Lectures)

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7
Q

Involves using evidence from the senses as the bases for conclusions (empirical method/research).

A

Empiricism

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8
Q

The Scientific Process Steps

A
  1. Identify a question
  2. Form a hypothesis & Gather information
  3. Test hypothesis by conducting research
  4. Analyze data
  5. Build a body of knowledge

— If the data you collected support the hypothesis, you experiment supported your hypothesis. It is supporting your theory. If not, revise theory and come up with new hypothesis.

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9
Q

A tentative explanation or prediction about a phenomenon (given a theory, I would expect this outcome).

A

Hypothesis

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10
Q

A set of formal statements that explain how and why certain events are related to one another (big picture).

A

Theory

“Attachment Theory”
— how humans attach throughout their lives

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11
Q

After viewing a behaviour, propose an explanation that makes sense in the context.

eg. A person lied down in the bench because they are tired.

A

Hindsight Understanding

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12
Q

Test possible explanations through scientific method.

eg. To find out why a person lied down on the bench, you’d do an experiment or survey.

A

Hypothesis-testing

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13
Q

What makes a good theory?

A

— Organized Information
— Testable (falsifiable)
— Predictions are supported by research
— Law of Parsimony

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14
Q

The idea that all things being equal, the simplest explanation is the best.

A

Law of Parsimony

aka Occam’s Razor

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15
Q

How do we get our data?

A

Obtain information related to hypothesis.

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16
Q

Precise, repeatable methods of measurement.

A

Scientific Observation

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17
Q

Standing outside your building and realizing it’s cold outside.

A

Casual Observation

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18
Q

Any characteristic that can vary (measurable).

A

Variable

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19
Q

Define a variable in terms of specific procedures used to produce or measure it.

Concrete and measurable terms.

A

Operational Definition

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20
Q

Always produce the same score when measuring the same thing (good measurement).

A

Reliability

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21
Q

Must be conceptually related to the property of study (good measurement).

A

Validity

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22
Q

Ability of a measure to detect the conditions specified in the operational definition (good measurement).

“powerful” way to measure

A

Power

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23
Q

Participants report on their own knowledge, beliefs, feelings or behaviour (types of measures).

eg. questionnaire or interview

A

Self-report

24
Q

A downside in using self-report. Desire to make good impression.

A

Social Desirability Bias

— don’t ask leading questions
— include questions for dishonesty
— ask someone else in their life

25
Q

Observers record observable behaviour (types of measures).

Requires operational definition.

Observers must be trained to consistently code their observations.

A

Observational

26
Q

Issues with overt behaviour:

A

Demand Characteristics
— observational setting that make people behave as they think that they should
— participants can change their behaviour when observed

27
Q

Make use of pre-existing records or documents (types of measures).

A

Archival Measures

— limited to records that already exist

28
Q

Specialized tests designed by psychologists to measure particular variables (types of measures).

A

Psychological Tests

29
Q

Examples of Psychological Tests:

A

Personality Tests — measure personality traits

Intelligence Tests — measure performance on intelligence testing tasks

Neuropsychological Tests — help diagnose abnormal brain function

30
Q

Seek to explain how we behave especially in natural environments (types of research).

eg. case studies, naturalistic observation, surveys

A

Descriptive Research

— all variables measured
— natural contexts
— extraneous factors not controlled

31
Q

Issues with Case Studies (type of descriptive research):

A

— poor method of determining cause-effect relationships
— generalizability is questionable
— researcher bias (if you are only measuring one person, all measurements are bias)

32
Q

Observing people in their natural environment (type of descriptive research):

eg. Jane Goodall observing chimpanzees in the wild

A

Naturalistic Observation

33
Q

Advantages of Naturalistic Observations:

A

— rich description of behaviour

— can avoid demand characteristics

34
Q

Limits of Naturalistic Observations

A

— ethical problems
— long periods to get single measure
— difficult to study particular behaviours

35
Q

The entire set of individuals about whom we wish to draw a conclusion.

eg. university students

A

Population

36
Q

A subset of individuals drawn from a population.

eg. 1000 students from each university

A

Sample

37
Q

A sample that reflects the important characteristics of the population.

eg. It should include all characteristics majors, genders, races, etc.

A

Representative Sample

38
Q

Method of sampling where every member of population has an equal probability of being chosen to participate.

eg. random number generator choosing students across university

A

Random Sampling

— not always possible but it’s okay if it doesn’t matter, multiple experiments conducted on different samples have similar results, similarity of sample and pop’n is reasonable

39
Q

Describing the center of the data.

A

Central Tendency

40
Q

Average value of all measurements.

A

Mean

41
Q

Value of middle of the distribution.

A

Median

42
Q

Value of the most frequently observed measurement.

A

Mode

43
Q

Normal Distribution

A

— aka Gaussian distribution, bell-curve

— symmetrical, central peak, trails off to both sides

44
Q

How much our measurements differ from one another:

A

Variability

45
Q

Value of largest measurement in a frequency minus the smallest.

A

Range

46
Q

Describes the average difference between the measurements in a frequency distribution and the mean of the distribution.

A

Standard Deviation

47
Q

Positively Skewed

A

Mode > Median > Mean

48
Q

Negatively Skewed

A

Mean > Median > Mode

49
Q

Box Plots

A

— box covers two quartiles of data
— box is 50% of data (interquartile)
— line inside shows the median

50
Q

Looking for an association between two (or more) measured variables (types of research).

A

Correlational Research

51
Q

“Does X cause Y or does Y cause X?”

A

Bidirectionally Problem

52
Q

X might be causing Y but maybe there’s a third variable that is causing X and Y— variable Z.

A

Third Variable Problem

53
Q

Describe relationship between variables.

A

Correlation Coefficient (r)

— ranges from -1.0 to 1.0
— signs indicate direction
— absolute value indicate strength

54
Q

Advantages of Correlational Research:

A

— show strength of relationship
— can be used to make predictions using data you have; extrapolate
— identify real-world associations

55
Q

Disadvantages of Correlational Research:

A

— can’t assume cause effect relationship
— association not cause
— relationship may be from unmeasured variable

PSYC0 104 (3 decks)

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