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YEAR 1 Semester 2👩🏼‍🎓 > Research Methods⚗️ > Flashcards

Research Methods⚗️ Flashcards

1
Q

P value

A

Probability of finding effect in sample if no effect in population (unsystematic variation)
If probability less than 0.05 can reject null

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2
Q

CI

A

95% confidence interval around the mean difference

Range of scores likely to indicate the true population mean

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3
Q

T value

A

Calculation of p value based on calculation of t value

If mean difference increases then t value increases and p value decreases

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4
Q

Effect sizes

A

Indicate if differences are psychological significant (not just statistically)

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5
Q

Independent T test

A

Between participants

Difference between variables (continuous DV, categorical IV)

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6
Q

Independent t test df

A

Total sample size - 2
(Two means are used)

Data that can be freely varied and still get same descriptive statistics in the sample

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7
Q

Independent and dependent t test assumptions

A

Data approximately normally distributed (histogram clear skew, if not use non-parametric test)
No clear outliers (boxplot, points outside the box)
Spread of scores (variance) is relatively equal in both groups, error bars
Levene’s test affects accuracy of t test if not equal

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8
Q

Paired t test

A

Within participants

Difference between variables (continuous DV, categorical IV)

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9
Q

Paired t test df

A

Df=total sample size - 1
One mean used

Data that can be freely varied and still get same descriptive statistics in the sample

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10
Q

Levene’s test

Assuming variance

A

Not significant (p more than 0.05) no significant difference in variance in each group (assume equal variance)

Significant (p less than 0.05) significant difference in the variance in each group (do not assume equal variance)

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10
Q

Independent t and paired t reporting results

A

Group 1 were (significantly) better (mean, SD) than group 2 (mean,SD)
t (df) =T VALUE, p = SIG 2 TAILED VALUE

This suggests that group 1 were better than group 2

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12
Q

Cohen’s d

A

Interprets magnitude of an effect independent of the scale used
For both independent and paired t test

Use mean and SD for both groups/conditions
Larger value indicates more pronounced effect (can be negative if opposite direction)

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13
Q

Calculating effect sizes

A

After finding a significant effect in a null hypothesis

Calculate Cohen’s d using the Cohen’s d calculator
Compare value to levels of effect size and state magnitude of effect
Bigger effect sizes indicate more important effect

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14
Q

Pearson’s correlation

A

Relationship between two variables

Continuous IV and continuous DV

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15
Q

Scatterplot relationship conclusions

A

How much trend resembles a linear pattern

Variation in x explained by differences in y scores or vice versa
Relationship between x and y can be explained by z
Relationship is chance

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16
Q

Correlation coefficient

A

Measure of effect

Direction (positive or negative) and strength of relationship (the more it resembles a straight line, between 0 and 1)

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17
Q

Correlation value strengths

A 
R= 0.01-0.39 weak
R= 0.40-0.69 moderate 
R= 0.70-0.99 strong
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18
Q

Pearson’s correlation assumptions

A

Data normally distributed (histogram clear skew, if not use non-parametric test)
No clear outliers (boxplot, points outside the box)
Linearity (plot on scattergraph to check)

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19
Q

Pearson’s correlation df

A

Total sample size (N) -2

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20
Q

Pearson’s correlation shared variance

A

R squared
Variation in scores in one variable that can be explained by variation in the other variable
Stronger relationship = more overlap and shared variance

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21
Q

Pearson’s correlation reporting results

A

The findings show a (STRENGTH AND DIRECTION OF CORRELATION from TEST SCORE) between A and B
The relationship was (SIGNIFICANT OR INSIGNIFICANT),
r (df) = TEST SCORE, p= SIG 2 TAILED
This shows that A…

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22
Q

What happens if p is 0.000

A

You write p< .001

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23
Q

Chi squared test

A

Relationship between variables

Categorical IV and categorical DV (transformed from continuous)

24
Q

Calculating chi squared test

A

Compare observed and expected values, bigger difference indicates larger Chi-squared value (more likely to reject null)

25
Q

Chi squared assumptions

A

No more than quarter of cells should have expected value more than 5
No individual cell should have expected value more than 1
Numbers in each cell should be independent, categories are mutually exclusive

26
Q

Cramer’s v effect sizes

A

Less than 0.10 trivial

  1. 10-0.30 small
  2. 30-0.50 medium
  3. 50+ large

Larger indicates more important relationship (chi squared)
Shared variance= v squared

27
Q

Reporting cramer’s v for chi squared

A

Cramer’s v =
This is interpreted as a (small/medium/large) effect
( x100)= percentage of the variation in A explained by B

28
Q

Report chi squared

A

In the sample, % of A and % of B did something
Chi squared test showed a (significant) relationship between two variables
xsquared (df, N=NUMBER IN SAMPLE)=CHI SQUARE VALUE, P=ASYMPTOTIC SIGNIFICANCE
This suggests that A is more likely to…

29
Q

Non parametric tests

A

Not normally distributed (check with histograms)
Uses ranks (focus where score stands in relation to others)
Less powerful, median most appropriate

30
Q

Parametric tests with their non parametric equivalents

A

Independent t -Mann Whitney
Paired t test-Wilcoxon
Pearson’s correlation- Spearman’s Rho

31
Q

Mann Whitney

A

Alternative to independent t test,
Compare mean ranks of two independent groups (between)
Categorical and continuous

Ordered according to score (temporarily disregard group)
Rank scores in order, average ranks of duplicate scores

32
Q

Reporting Mann Whitney and Wilcoxon

A

There was a (significant) difference between A (median) compared to B (median)
Mann Whitney U= MANN WHITNEY DATA, p=ASYMP 2
This suggests that…

WILCOXON- use Z instead of U
Z value negative value can be stated as positive

33
Q

Wilcoxon signed rank

A

Alternative to paired t test
Compare mean ranks of participants who scored higher on (within)
Categorical and continuous
condition 1 to mean ranks of those who scored higher on condition 2

34
Q

Spearman’s Rho

A

Alternative to Pearson’s correlation
Compare correlation using ranked scores

Continuous IV and continuous DV

35
Q

Reporting spearman’s Rho

A

Spearman’s correlation showed that there is a (strong positive) relationship between A and B
Rs= CORRELATION COEFFICIENT MYATTRAC, P=SIG 2 TAILED
This suggests that…

36
Q

Epistemology

A

Aim of research is to understand or gain knowledge about the world (patterns, behaviour, principles)

37
Q

Approaches to research (philosophical)

A

Positivism- only one reality, uncover through observations
Post positivism-acknowledge need for falsification, use observation
Phenomenological- reality socially constructed, use dialogue to make sense of subjective experience
Constructionism- not one reality, socially/culturally produced through interaction
Relativism-not one reality, relative to historical, cultural and social context

38
Q

Methodology

A

Strategy or approach to research

Qualitative or quantitative

39
Q

Quantitative

A

More positivist, uncover one reality
Deductive- start with theory, specific hypotheses, see if reality makes sense
Analysis- constructs (thoughts, behaviour)of interest are coded to numbers

40
Q

Qualitative

A

Relativist, not one reality, subjective experience
Inductive-observations from people, form more general theory. Aim to find general themes or viewpoints
Analysis-focus on content, emphasis on words not numbers

41
Q

Qualitative methods

A

Direct data collection- interviews, focus groups, questionnaire
Indirect data collection-observations, analysis of online material

42
Q

Qualitative criticisms

A

Subjective, influenced by personal bias
Does not represent population (but doesn’t aim to)
Cannot be replicated (does not aim to)
Not systematic

43
Q

Qualitative research methods-interviews

A

STRUCTURED-predetermined questions in order, ask same questions to all to compares minimise bias, descriptive or exploratory
SEMI STRUCTURED- Flexible schedule of questions, few are set, open to new directions. Inductive approach, explanatory or exploratory

44
Q

Conducting interviews good practice

A 
Simple language, no jargon 
Prompt when necessary 
Rapport for comfort 
Active listening, nodding 
Body language, eye contact
45
Q

Focus groups

A

Group dynamic, reflect on viewpoint. Range of perspectives
Avoid sensitive topics (may withhold)
Researcher as facilitator (steer it)

46
Q

Qualitative research methods- observations

A

NATURALISTIC-everyday setting, unaware of observation. Can be archived data. No direct manipulation
PARTICIPANT OBSERVATION-researcher immersed in setting/activities
NON PARTICIPANT OBSERVATION-Researcher observes, no active part

47
Q

Ethical and practical considerations of research methods

A

Consent-problem in naturalistic setting, knowledge can influence findings
Confidentiality/anonymity-how answers will be used
Debrief-a problem in naturalistic setting
Uncertain if have all data, if everything has been raised
Researcher/participant bias

48
Q

Four main steps in data analysis (content/theme)

A

Anchor data to research question
Transcribe data- orthographic (verbatim) vs non orthographic (paralinguistics etc)
Initial reading of data- themes and how interviewer may have shaped data
Systematic data- driven by research question,cyclical refinement
Aim to find structure

49
Q

Content analysis

A

Combines qualitative and quantitative

Extract common topics and themes, count how often they occur
Deductive (predefined areas) or inductive (emerges from data)

50
Q

Content analysis steps

A 
Familiarise with data 
Generate initial codes 
Search for higher order themes 
Review topics and themes 
Inter rater reliability check
Count occurrences of each topic/ theme 
Write report
51
Q

Codes for content analysis

A

Code should fit with data
Aim for as few codes as possible but still represent the data
Present only relevant info in write up

52
Q

Thematic analysis

A

Extract common topics and themes
Use quotes to illustrate key aspects covered in wider themes
Distinction between major and minor themes

53
Q

Grounded theory

A

Start with data and develops themes to generate theory (inductive)

54
Q

Reflexivity

A

Important in qualitative analysis to be reliable and systematic
Aware of researcher’s influence on data

55
Q

phenomenological analysis

A

Analysis of a subjective interpretation of a topic

56
Q

df for everything

A

Independent t test -2
Paired t test -1
Pearsons correction -2
chi square Says it on the column

YEAR 1 Semester 2👩🏼‍🎓 (5 decks)

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