Brainscape's Knowledge GenomeTM

Browse over 1 million classes created by top students, professors, publishers, and experts.


See full index

Psychology > Research Methods 2 > Flashcards

Research Methods 2 Flashcards

You may prefer our related Brainscape-certified flashcards:
Psychology 101 flashcards GRE® Psychology flashcards AP® Psychology flashcards
1
Q

Features of a science

A

Theory construction
hypothesis testing
empirical method
paradigms
replicability
objectivity
falsifiability

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

what is a science

A

knowledge and evidence
using scientific method

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

scientific method

A

make an observation

develop an explanation

test empirically

do findings fit theory

if not then develop new explanation

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

paradigms

A

set of assumptions, theories, methods, terminology shared by psychologists e.g. approaches

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

Paradigm shift

A

When an established paradigm is challenged to the point that a new one takes its place

Thomas Kuhn - normal science- theory is dominant
-scientific revolution - caused by disconfirming evidence for normal
-paradigm shift - normal is overthrown - theories and methods change

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

social sciences - paradigms

A

Kuhn - science has single paradigm

social sciences lack universally accepted paradigms due to too many conflicting approaches so psychology is deemed pre-science

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

Falsifiability

A

theory cannot be considered scientific unless possible for it to be proven untrue

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
8
Q

Karl Popper

A

all swans are white - no matter how many instances of white swans we observe, this does not justify conclusion that all swans are white

should seek disproof rather than examples that confirm theory

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
9
Q

null hypothesis

A

e.g. not all swans are white

researchers should aim to reject null e.g. if no black swans are sighted this strengthens theory

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

pseudoscience

A

Popper - cannot be falsified e.g. freud - unscientific

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

Theory construction

A

set of general laws or principles that explain a specific behaviour

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

Hypothesis testing

A

testable expectations

if scientist fails to support hypothesis then the theory requires modification

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
13
Q

empirical method

A

refers to any methods that provide evidence based on direct experience rather than unfounded belief

reports on world how it really is

well controlled and objective

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
14
Q

empirical method in psychology

A

the variables that are measured in psych can be difficult to directly observe e.g. happiness/intelligence levels

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
15
Q

Objectivity

A

removal of any bias - results collected in a way that is independent of researcher

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
16
Q

why objectivity is important feature of science

A

builds confidence that findings represent real effect rather than views of investigator

helps ensure methods used were well controlled and high internal validity

identify scientific fraud

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
17
Q

Replicability

A

repeatability to determine validity and reliability

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
18
Q

why replicability is important feature of science

A

ensures results are reliable and builds confidence that finding is trustworthy and represents real effect

ensures methods are standardised improving validity

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
19
Q

Abstract

A

overview of entire investigation

allows reader to decide whether or not to read rest of report

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
20
Q

Introduction

A

review of previous research so reader knows what research has already been done

should follow logical flow of ideas to persuade about reasons for carrying out the study

also state aims and hypothesis

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
21
Q

Method

A

design, participants, apparatus, procedure, ethics

should be enough detail for someone to replicate the study

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
22
Q

Results

A

descriptive stats and inferential stats

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
23
Q

How to write results section

A

1) always be very clear on precisely what the findings show with fully operationalised names to conditions and measurements

2) give full information including all numbers and all details that led you to choose critical value

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
24
Q

Discussion

A

1)summary of results - statistically significant?
2)relationship to previous research
3)consider methodology and improve suggestions
4)implications for psychological theory
5)suggestions for practical applications
6)suggestions for future research

Selling Peanuts (to) Monkeys In Pretty Fleeces

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
25
Q

References

A

full details of any books, journals or websites mentioned in report

How well did you know this?
1
Not at all
2
3
4
5
Perfectly
26
Q

Case studies

A

investigation of single individual, group, institution or event

27
Q

Case study - advantages

A

+provide rich detailed data
complex interaction of many variables - helps identify what may have been overlooked

+allows behaviour that would be unethical to deliberately manipulate to be studied
e.g. clive wearing

28
Q

Case study - disadvantages

A

-may lack validity
population validity due to focus on small sample
prone to social desirability bias

-ethical issues
informed consent e.g. not able to fully comprehend or too young e.g. clive wearing and little hans
confidentiality e.g. easily identifiable due to unique characteristics

29
Q

Content analysis

A

observational study where people are observed indirectly - focuses on communications people have produced such as speeches, diaries, films, books etc
coding system is used to convert qualitative to quantitative

30
Q

Sampling method for content analysis

A

Selected randomly or identify characteristics

Every page or every nth page

Time sampling or event

31
Q

Coding

A

Placing into clearly operationalised categories and use tallying (quantitative) or describing examples in each category (qualitative)

32
Q

How to conduct content analysis

A

1) gather materials to be analysed using sampling method
2) read and reread to familiarise
3) form key categories and operationalise
4) tally up number of times each one occurs
5) draw conclusions

33
Q

Content analysis advantages

A

+easy to replicate
+high ecological validity

34
Q

Content analysis disadvantages

A

-suffers observer bias
-likely to be ethnocentric - culture influences interpretation

35
Q

Thematic analysis

A

Identifying recurring themes that emerge from the data and organising them

Allows data to be summarised - remains qualitative

36
Q

How to conduct thematic analysis

A

1) familiarise
2) break data into meaningful units - small bits of text that convey meaning equivalent to sentences or phrases
3) assign label to each unit
4) combine labels into broader themes
5) check by collecting new set of data and applying themes
6) write up report with themes as headings

37
Q

Thematic analysis advantages

A

+maintains much of detail from original material
+high ecological validity

38
Q

Thematic analysis disadvantages

A

-Time consuming
-suffers observer bias

39
Q

Assessing validity - face

A

Whether it looks like it is measuring what the researcher intends to

40
Q

Assessing validity - concurrent

A

Whether findings match those from a more recognised and established test of same topic

Must correlate strongly +0.8

41
Q

Improving validity

A

Questions removed, revised or rewritten

42
Q

Assessing reliability - test-retest

A

Same test or measurement given to same participants on two separate occasions

0.8 correlation

43
Q

Assessing reliability - inter-observer reliability

A

The extent to which there is agreement between two or more observers

0.8 correlation

44
Q

Improving reliability

A

Inter observer - behavioural categories weren’t operationalised clearly enough

Test-retest - questions were ambiguous or too complex

45
Q

Nominal data

A

Named categories where frequencies are counted in each category

Discrete

Mode

Bar chart

+basic and simple
-less precise

46
Q

Ordinal data

A

Data placed in an order with no fixed intervals between units

Subjective

E.g. ranking, rating, test score

Median

Histograms and line graphs

+more precise than nominal
-less precise than interval

47
Q

Interval data

A

Data based on scale that has fixed intervals between each unit

E.g. time in seconds, distance in metres

Mean

Histograms and line graphs

+More objective and precise
-not basic and simple

48
Q

Probability

A

Numerical measure of the chance that certain events will occur

Number of particular outcomes divided by number of possible outcomes

49
Q

Significance

A

A result that is strong enough for us to be confident it represents a real effect

50
Q

Stringent level

A

P < 0.01

99%

Medicine

51
Q

Standard level

A

P< 0.05

95%

Psychology

52
Q

Lenient level

A

P < 0.1

90%

Pilot study

53
Q

Type 1 error

A

Optimistic - false positive

Accepting a hypothesis that is false

Likelihood increased when lenient significance level

54
Q

Type 2 error

A

Pessimistic - false negative

Rejecting a hypothesis that is true

Higher likelihood when stringent significance level

55
Q

Choosing a stats test

A

Difference Relationship

                      Unrelated               Related             Related

Nominal: Chi squared Sign test Chi squared

Ordinal : Mann- Whitney Wilcoxon Spearman’s

Interval: Unrelated T Related T Pearson’s

Chi squared - association + unrelated

56
Q

Sign test

A

Number of pluses =

Number of minuses =

Lower number = calculated s value

S value must be less than critical to be significant

57
Q

Chi squared - degrees of freedom

A

Rows x columns

Calculated value must be more than critical value to be significant

58
Q

One tailed hypothesis

A

Directional

59
Q

Two tailed hypothesis

A

Non directional

60
Q

Template stats answer

A

The result of the statistical test is/isn’t significant

Therefore the null is rejected/accepted

And the hypothesis is accepted/rejected

This is because the calculated value (X) is greater than the critical value (X)

At the p=0.05 level of significance when N/Df = (X) for a one/two tailed test

This means there is/isn’t a significant ————— between X and Y in terms of their Z

61
Q

Chances of making type one error

A

The given level of significance (e.g. P=0.05) tells us the chance (e.g. 5%)

62
Q

Chances of making a type 2 error

A

If results aren’t significant look across table to whether significant at a more lenient level

63
Q

Brief

A

Read to participants before hand

Asking for consent

64
Q

Debrief

A

Read after

Thank them
Reveal true aim
Ethical considerations
Any questions?

Psychology (7 decks)

Brainscape helps you reach your goals faster, through stronger study habits.
© 2024 Bold Learning Solutions. Terms and Conditions