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Psychology SL IB 2020-22 > 1b. Quantitative research methods > Flashcards

1b. Quantitative research methods Flashcards

1
Q

What is the goal of an experiment?

A

To determine a cause and effect relationship between two variables

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2
Q

Confounding/extraneous variables

A

They contribute to bias as they could potentially influence relationship.

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3
Q

How do you control confounding variables?

A

They are eliminated or kept constant

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4
Q

Lab/True experiment

A

When independent variable is manipulated to study effect on dependent variable

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5
Q

Characteristics of lab experiments

A
  • High degree of control/standardized
  • Cause-and-effect is established
  • Random allocation to remove demand characteristics
  • Quantitative data is collected
  • May not be realistic if there is too many confounding variables
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6
Q

Field experiment

A

Studies that occur outside lab conditions

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7
Q

Characteristics of field experiments

A
  • Cannot control confounding variables
  • Cannot be easily replicated
  • High ecological validity
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8
Q

Quasi experiment

A

IV is not manipulated. They are naturally pre-existing differences like age, gender, ethnicity

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9
Q

Characteristics of quasi experiments

A
  • No cause and effect established
  • Participants are not randomly allocated
  • Setting can be lab or field
  • Implies casual relationship
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10
Q

Natural experiment

A

Behavior is measured before and after a variable is introduced eg. behavior of smokers after cigarettes were banned

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11
Q

Characteristics of natural experiments

A
  • No cause and effect established
  • Participants are not randomly allocated
  • Setting can be lab or field
  • Implies casual relationship
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12
Q

Hypothesis

A

Prediction of how IV will affect DV

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13
Q

Null hypothesis

A

States there is no significant difference i.e. no relationship between IV and DV

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14
Q

Experimental hypothesis + types

A

Predicts a relationship between IV and DV

  • One tailed: Direction of relationship is specified
  • Two tailed: No direction specified
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15
Q

Difference between aim and hypothesis

A
  • Aim is just IV, DV and target population

- Hypotheses includes operationalized IV and DV

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16
Q

What are limitations of experiments

A
  • Artificial set-up
  • May not reflect real life
  • May lack ecological validity
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17
Q

What are the 3 sources of bias or error?

A
  1. Participant
  2. Researcher
  3. Sampling
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18
Q

Demand characteristics

A

Occur when participants act differently because they know they’re in a study

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19
Q

Expectancy effect

A

Participants attempt to guess researcher’s hypothesis with the aim of helping the researcher. (They might act a certain way or try to give right answers)

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20
Q

Screw you effect

A

Participants attempt to guess the researcher’s hypothesis but only in order to destroy credibility of study

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21
Q

Social desirability effect

A

Participants answer in a way that makes them look good to the researchers. Done to avoid embarrassment or judgement

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22
Q

How can you avoid demand characteristics?

A

Single blind studies. Experiment where researchers know which participants are receiving which treatment but participants don’t know which condition they are in

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23
Q

Participant variability and how to control

A

Characteristics of sample affect DV and can only be controlled by randomly allocating people to groups

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24
Q

When might sampling bias occur and what will it result in?

A
  • When psychologists use non-probability sampling technique (everything except random sampling), there may be bias
  • May cause some members to be less likely to be included than others
  • Participant variables may not be representative and hence influence outcome
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25
Researcher bias
When experimenters see what they are looking for
26
Types of researcher bias
1. Confirmation bias: Paying attention to info that agrees and discount information that contradicts it 2. Publication bias: Researchers may manipulate data for quicker publications as it is expected of them to publish for credit
27
How to control for researcher bias
Double blind control. Both participants and researcher do not know who is receiving which treatment
28
Research designs
Overall strategy that a researcher uses to investigate the research problem
29
Research designs: Repeated measures
One sample of participants receive all conditions of an experiment
30
Research designs: Strengths of repeated measures
- Individual is only compared to themselves so participant variable is controlled - Requires lesser number of participants
31
Research designs: Limitations of repeated measures
- Order effects: Differences in participant responses result from order in which they participate in conditions - Demand characteristics are not controlled
32
Research designs: 3 types of order effects
1. Fatigue effect: Decrease in performance in later conditions is because they are tired or bored 2. Interference effect: When first condition may influence the outcome of the second 3. Practice effect: Improvement in performance as they have developed the skill
33
Counterbalancing
Technique used to deal with order effects. eg. Sample is divided in half and both groups attempt both conditions but in different orders
34
Research designs: Independent measures
Random allocation of participants
35
Research designs: Pros and cons of independent measure
``` Pros: - Less chance of order effects - Less chance of demand characteristics as participants cannot guess (only exposed to one condition) Cons: - Affected by participant variables - Requires a lot more participants ```
36
Research designs: Matched pair design
Matches participants who have equal characteristics and then divides according. Usually depends on DV (eg. level of memory)
37
What is not matched pair design?
Matching to ensure there are no extraneous variables like age, gender and race
38
When is matched pair design used?
When there is small groups as random allocation will not be sufficient for group equivalence
39
Cross sectional study
Researcher compares two or more groups on a specific variable at a specific time i.e. short-term
40
Longitudinal study
Where a researcher measures change in an individual over time
41
Retrospective study
Participant is asked about past behaviour
42
Limitations of retrospective study
- Relying on someone's memory - Not possible to verify information - Social desirability effect - No cause and effect
43
Prospective study
Measures a variable at beginning and then watches effect overtime
44
Limitations of prospective study
- Takes much longer to carry out | - Participants may get tired, bored or drop out
45
Reliability
Consistency of a measure. Degree to which a study is free of random error.
46
Test-retest reliability
Obtaining the same results across time with the same population
47
Validity
Degree to which a test measures what is claims to measure
48
Internal validity
When experiment is controlled to ensure only IV is affecting DV. Higher degree of control= higher internal validity
49
Where can high internal validity be observed?
Lab experiments
50
External validity and the types
Extent to which results can be generalized beyond sample tested 1. Population validity 2. Ecological validity
51
Population validity
Describes how well sample can be generalized to target population. High when sample is representative
52
Ecological validity
Looks at experimental environment and determines how much it influences behaviour. Are they representative of conditions in the wider world?
53
Where can high ecological validity be observed?
In field experiments
54
Construct validity
Characterizes quality of operationalization.
55
Name some threats to internal validity
1. Selection: Groups are not equivalent 2. History: Outside events can affect behaviour especially in long studies 3. Demand characteristics 4. Instrumentation: eg. Natural human errors like when observing 5. Testing effect 6. Experimental mortality
56
Correlation
Measure of linear relationship between 2 variables
57
Positive correlation
Increase or decrease in BOTH variables at the same time
58
Negative correlation
One increases while the other decreases (inverse tendency)
59
What is the term for no relationship between variables?
Zero correlation
60
Correlation coefficient
Number used to denote correlation between two variables. Ranges from -1 to 1 where the extremes are perfect correlations
61
Interpretation if correlation coefficient is between 0.30-0.49
Probably medium relationship
62
Interpretation if correlation coefficient is between <0.1
Negligible
63
Curvilinear relationships
When 2 variables increase or decrease but only up to a certain point. After that, there will be change in the relationship

Psychology SL IB 2020-22 (10 decks)

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