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psychology revision > Need To Know Research Methods > Flashcards

Need To Know Research Methods Flashcards

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1
Q

Co- variables

A
  • two measured variables in a correlational analysis

- variables must be continuous.

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2
Q

Content analysis

A
  • method used to analyse qualitative data

- Allows researcher to take qualitative data & turn it into quantitative data

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3
Q

Aims

A

-statement of what researcher intends to find out in research study.

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4
Q

Hypothesis

A

-precise & testable statement about assumed relationship between variables

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5
Q

Directional hypothesis

A

-States direction of predicted difference between two conditions or two groups of participants

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6
Q

Non directional hypothesis

A
  • Predicts simply theres a difference between two conditions or two groups of participants without stating direction of difference.
  • Two tailed predicts effect between variables but not which way eg therell be an effect between amount of energy drink consumed & number of words spoken in following 5 mins
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7
Q

Sampling

A
  • method used to select participants like:
  • random sampling
  • opportunity
  • volunteer sampling
  • sample behaviours in observation like event or time sampling.
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8
Q

Population

A
  • group of people that researcher is interested in
  • group of people from whom sample is drawn.
  • group of people about whom generalisations can be made
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9
Q

Random sample

A

-sample of participants produced using random technique such that every member of target population being tested had equal chance of being selected

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10
Q

Pilot study

A
  • Small trial versions of proposed studies to test effectiveness and make improvements
  • helpful in identifying potential issues early
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11
Q

Qualitative data

A
  • non numerical language based data collected through:
  • interviews
  • open questions
  • content analysis
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12
Q

Investigator effects

A

-Occur when researcher unintentionally or unconsciously influences outcome of research they’re conducting.

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13
Q

Reliability of content analysis

A
  • Analysis can be repeated

- reliability is measured using inter rater reliability

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14
Q

Directional hypothesis

A

-researchers predicting direction or effect one variable will have on another be it positive or negative

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15
Q

Evaluation - repeated measures

Strengths and weaknesses

A
  • Strengths- no individual differences as peoples scores in one condition are compared to their scores in a different condition, fewer participants required
  • Weaknesses- time consuming as all participants have to do both conditions
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16
Q

Evaluation - independent groups

Strengths and weaknesses

A
  • Strengths - quicker as two groups cans do task simultaneously
  • no order effects;all participants start condition naive
  • Weakness - individual differences can affect results
  • eg people in one condition are better at maths than those in other condition
  • requires more participants however many that researcher obtains has to be divided into 2 groups
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17
Q

Evaluation- matched participants

Strengths and weaknesses

A
  • Strengths- limits effect of individual differences
  • as participants should be matched on important characteristics
  • done quickly both groups can complete tasks simultaneously
  • Weaknesses - hard to find people that are good match because there’ll still be differences
  • requires large number of participants
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18
Q

Laboratory experiment-

A
  • experiment conducted in special environment (lab) where variables can be carefully controlled
  • researcher manipulated IV
  • measures DV
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19
Q

Field experiment

A
  • controlled experiment conducted in any environment outside of lab.
  • Researcher manipulates IV
  • measures DV
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20
Q

Difference between lab and field experiment

A
  • lab experiment conducted in special environment
  • unlike field
  • lab experiments-participants aware they’re taking part in an experiment
  • field they’re not usually aware
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21
Q

Similarity between lab and field experiment

A
  • both IV is manipulated by experimenter

- Both make sure IV is manipulated deliberately to draw causal conclusions from it

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22
Q

Example of lab experiment

A
  • loftus and Palmer study of eyewitness testimony
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23
Q

Example of field experiment

A

-Johnson and Scott’s 1976 study of weapon focus

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24
Q

Advantages and disadvantages of lab experiment

A
  • high degree of control - increases validity of study
  • participants aware of being studied
  • more likely to lead to demand characteristics
  • reduces validity
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25
Q

Advantages and disadvantages of field experiment

A
  • participants aren’t aware of being studied so behaviour is more natural
  • less control
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26
Q

Sampling error

A

-amount of difference between sample and population

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27
Q

Theory

A

-Organised, testable explanation of phenomena

28
Q

Hindsight bias

A

-Tendency of people to overestimate their ability to predict an event after it happened

29
Q

Ordinal data

A
  • data thats presented in rank order

- e.g. places in a beauty contest, or ratings for attractiveness

29
Q

Case studies A01

A

-in-depth investigations of single person, group, event or community.

30
Q

Correlation

A
  • Correlation means association

- measure of extent to which two variables are related.

31
Q

Covert observations A01

A

-researcher pretends to be an ordinary member of group and observes in secret.

32
Q

Overt observations

A
  • researcher tells group he/she is conducting research

- i.e. they know theyre being observed

33
Q

Meta analysis

A
  • systematic review involves identifying an aim
  • searching for research studies that have addressed similar aims/hypotheses.
  • done by looking through various databases
  • decisions are made about what studies are to be included/excluded.
34
Q

Meta analysis strengths and weaknesses

A
  • Strengths:
  • Increases validity of conclusions drawn as they’re based on a wider range.
  • Weaknesses:
  • Research designs in studies can vary so they aren’t truly comparable.
35
Q

Validity

A
  • whether observed effect is genuine

- represents what’s actually out there in the world.

36
Q

Ecological validity

A

-extent to which findings from a research study can be generalised to other settings / real life.

37
Q

Temporal validity

A
  • extent to which findings from research study can be generalised to other historical times.
38
Q

Reliability

A
  • measure of consistency
  • if particular measurement is repeated
  • and same result is obtained then its described as being reliable.
39
Q

Test-retest reliability

A
  • Assessing same person on two different occasions

- shows extent to which test produces same answers.

40
Q

Empiricism

A
  • Info is gained through direct observation of expriment
41
Q

Objectivity

A
  • personal expectations shouldn’t effect what findings are recorded
42
Q

Replicability

A
  • previously recorded methods

- and procedures are retested to see if outcome is same

43
Q

Control

A
  • research attempts to find relationships through experimental methods which require degree of control eg we vary IV
  • observe its effects on DV
  • we must ensure all other conditions are same
44
Q

Scientific method

A
  • use of investigative methods that are:
  • objective
  • systematic
  • replicable
  • formulation
  • testing
  • modification of hypotheses based on these methods
45
Q

Statistical tests levels of measurement Nominal data

A

-are in separate categories like grouping people according to their favourite football team

46
Q

Statistical tests level of measurement interval data

A
  • measured using units of equal intervals

- like when counting correct answers or using any ‘public’ unit of measurement

47
Q

Chi squared steps

A

1- calculated value of x^2
Eg 1.984 -> compare with critical value
2- draw up a contingency table
3-
4- find observed value of chi squared (x^2)
Add all values in final column in table above eg 1.984
5- find critical value of chi squared (x^2)
Calculate degrees of freedom (df) by multiplying (rows-1) x (columns -1 ) = 1
look up values in table of critical values (on the right)
For a two tailed test df = 1 critical value of x^2 = 3.84 (p < 0.005)
6- state conclusion
As observed value (1.984) is less than critical value (3.84) we must accept null hypothesis (at p < 0.05) & therefore we conclude there’s no difference between men & women in terms of digit ratio

48
Q

Alternative hypothesis

A

-testable statement about relationship between two or more variables

49
Q

Probability

A
  • numerical measure of likelihood or chance that certain events will occur
  • statistic test gives probability that a particular set of data didn’t occur by chance
50
Q

Type 1 error

A

-occurs when researcher rejects a null hypothesis that’s true

51
Q

Type 2 error

A
  • occurs when researcher accepts a null hypothesis that was not true
52
Q

What does a statistical test determine

A
  • which hypotheses are true by either accepting or rejecting one of the hypotheses
53
Q

Null hypothesis no tailed

A
  • predicts therell be no effect between variables
  • eg energy drink consumed will not effect amount of words spoken in following 5 mins so there’ll be no significant different
54
Q

Chance

A
  • refers to something with no cause as it just happens
  • can’t be 100% certain that observed effect wasn’t due to chance but you can state how certain you are
  • we used a statistical test to find whether results are significant or due to chance
55
Q

Probability levels

A
  • psychologists use level of probability of 95%
  • expresses degree of uncertainty
  • means 5% chance of results occurring if null hypothesis is true
  • probability of 5% is recorded as p=0.05
  • probability is 5% or less which is written as p
56
Q

Significance

A
  • ‘true’ isn’t exactly correct word because actually statistics tests employ level of significance
  • means researcher can state that relationship between variables is due to more than just chance
  • they can accept alternative hypothesis
  • reject null hypothesis
57
Q

What is the acronym for carrots should come mashed with swede under roast potatoes in relation to statistical tests?

A
  • Chi-Square
  • Sign Test
  • Chi-Square
  • Mann Whitney U
  • Wilcoxon
  • Spearman’s rho
  • Unrelated T-Test
  • Related T Test
  • Pearson’s r
58
Q

Evaluate Repeated Measures Design

A
  • Counterbalancing is a way to deal with repeated measures
59
Q

Evaluate independent groups design

A
  • randomly allocate ppts into conditions

- evenly distribute ppt variables

60
Q

Evaluate matched pairs design

A
  • restrict amount of variables to match

- to make it easier or conduct pilot study to consider key variables that might be important to match

61
Q

Explain counterbalancing

A
  • Used to deal with extraneous factors caused by order effects when using repeated measures design
  • Eg rather than all 30ppts completing both conditions, we would split them up
  • 15 of them would complete condition A,then B and other 15 ppts would complete condition B, then A
  • order effects would be balanced out by opposing half participants due to fact they were split up rather than all 30ppts doing same thing
62
Q

What is lab experiment and how can we evaluate it ie strengths

A
  • investigate casual relationship between IV and DV under controlled conditions
  • well controlled, extraneous/confounding variables are minimised.
  • High internal validity allowing easy replication demonstrating external validity
63
Q

What is field experiment and how can we evaluate it

strengths

A
  • investigate casual relationship between IV and DV in more natural surroundings
  • less artificial
  • high in mundane realism
  • ecological validity as ppts arent usually aware they’re being studied
64
Q

What is natural experiment and how can we evaluate it

Strengths

A
  • investigate casual relationship between IV and DV in situations where IV cant be directly manipulated.
  • allows research where IV can’t be manipulated for ethical reasons
  • Allows studying of real problems
  • high mundane realism
  • ecological validity
65
Q

What is quasi experiment and how can we evaluate it

Strengths

A
  • investigate casual relationship between IV and DV in situations where
  • IV is a characteristic of a person (something we can’t change e.g. gender)
  • allows comparison of all types of people
66
Q

Stratified sampling

A
  • sampling technique where researcher divides or ‘stratifies’ target group into sections
  • each representing a key group (or characteristic) that should be present in final sample.

psychology revision (21 decks)

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