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Part A > Research Skills A > Flashcards

Research Skills A Flashcards

1
Q

What is pluralistic ignorance?

A

Linked to the bystander effect - people assume others will help, or think there is no danger if no-one is helping

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2
Q

Why do we need research?

A
  • studies and theories are underpinned by research
  • as the world changes we need to test new theories
  • to avoid myths
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3
Q

What does empirical mean?

A

Verifiable by observation or experience rather than theory or pure logic.

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4
Q

Describe the deductive reasoning technique

A

Reasoning from general statements to a logical and certain conclusion (TOP DOWN method)
- general argument –> specific conclusion

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5
Q

Describe the inductive reasoning technique

A

Reasoning from a single statement to the probable validity of a conclusion (BOTTOM UP method)
- specific argument –> general conclusion

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6
Q

What is the hypothetico-deductive method?

A

“A method of scientific inquiry in which the credibility or explanatory power of a falsifiable hypothesis is tested by making predictions on the basis of this hypothesis and determining whether these predictions are consistent with empirical observations. It is one of the most widely used scientific methods for disproving hypotheses and building corroboration for those that remain (APA, 2022

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7
Q

What 3 things must hypotheses be?

A
  • falsifiable
  • testable
  • precise
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8
Q

What are the 7 stages of the Hypotheoretico-Deductive method?

A
  1. identify a problem
  2. define the problem
  3. generate hypotheses to test the problem
  4. design the research
  5. collect the data
  6. analyse the data
  7. interpretation of the results
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9
Q

What is generalisability?

A

the extent to which findings can be generalised across a sample or population

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10
Q

What is replication?

A

The ability to repeat a study in the same way it was originally conducted.

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11
Q

Randomised Controlled Trials (RTC’s)

A
  • most rigorous form of research
  • used to measure the effect of an intervention by randomly assigning individuals
  • completed double blind
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12
Q

True Experiments

A
  • lab-based and fully controlled
  • standardised, random allocation and experimental manipulation
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13
Q

Quasi Experiments

A
  • similar to true experiments
  • lacks random assignment or full control over the IV
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14
Q

Correlational Studies

A
  • determines relation between 2 factors
  • non-manipulated variables
  • can observe natural variation
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15
Q

Questionnaires

A
  • objectively measure a concept
  • used to collect data in correlational studies
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16
Q

What is an independent variable? What are the 2 sub-categories?

A

Variable that is manipulated
- Experimenter variables
- Participant / subject variables

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17
Q

What is a dependent variable?

A

The outcome we are measuring. The subjects response to the IV

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18
Q

What is an extraneous variable?

A

Variables that potentially influence results but are bot of direct interest.
- they threaten validity and reliability

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19
Q

What is a continuous variable? Give an example

A
  • can take any value within a given range
  • temperature, levels of anxiety
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20
Q

What is a discrete variable? Give an example

A
  • can only take certain discrete (whole) values within a range
  • number of children, number of cars
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21
Q

What is a categorical variable? Give an example

A
  • when the value a variable takes is a category
  • gender, ethnicity, occupation
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22
Q

What does dichotomising continuous variables mean? What are some advantages and disadvantages?

A
  • converting continuous or discrete variables into categorical variables so they can be directly compared
    A = simplifies data analysis
    D = by simplifying it means that data isn’t always as good
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23
Q

What is within-subjects design?

A

Can be called repeated measures
Using the same participants in all conditions

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24
Q

List advantages and disadvantages of within-subjects design

A

A - better control for individual differences
A - less participants to recruit
D - causes order effects
D - causes demand effects
D - concerns about attrition (people dropping out)

25
Q

What is between-subjects design?

A

Can be called independent groups
Using different participants in each condition

26
Q

List advantages and disadvantages of between-subjects design

A

A - no order effects
A - less demand effects
D - need to recruit more participants
D - can’t control for individual differences

27
Q

What is a population?

A

A group that shares a common set of characteristics; it is the wider group you wish to learn about

28
Q

What is a sample?

A

The group selected from the population to participate in your research

29
Q

What are the 3 types of probability sampling?

A
  1. simple random sampling
  2. systematic random sampling
  3. stratified random sampling
30
Q

What are the 2 types of non-probability sampling?

A
  1. opportunity / convenience sampling
  2. self-selecting and online sampling
31
Q

What are ethics?

A

Responsible and morally right conduct

32
Q

What event resulted in the Nuremberg Code (1947) being developed?

A

The trial of 23 physicians from the German Nazi Party for crimes against humanity on unwilling prisoners of war

33
Q

What is ‘risk’?

A
  • any potential physical or psychological harm
  • self-esteem, personal values, illegal or deviant behaviour
34
Q

What is ‘valid consent’?

A
  • agreement to freely and voluntarily participate in research
35
Q

What is ‘Gillick Competence’?

A

Used in medical law, so that under 16’s can consent to medical procedures without parental consent

36
Q

What is nominal data? Provide examples

A
  • refers to categorical data
  • gender, ethnicity, job type
  • numbers are assigned but have no rank importance
37
Q

What is ordinal data? Provide examples

A
  • a scale to measure ordre or rank
  • size of number is representative but, it doesn’t inform us of the distance between 2 numbers
  • position in a race: 1st, 2nd
38
Q

What is interval data? Provide examples

A
  • a scale where differences between points are equal, but there is no ‘true zero’
  • temperature
39
Q

What is ratio data? Provide examples

A
  • a scale where the differences between numbers are equal, but there IS an absolute zero
  • height, scores on a test, speed of a car
40
Q

What are descriptive statistics?

A
  • summaries data using numbers or graphs
  • summaries all levels of data
  • central tendency
  • allows comparison between studies
41
Q

What are inferential statistics?

A
  • using the data to make inferences and generalisations
  • interval and ratio data are required
42
Q

What is skewness?

A

The extent to which a histogram is lopsided rather than symmetrical

43
Q

Which way is positive skew?

A

Towards the left

44
Q

Which way is negative skew?

A

Towards the right

45
Q

What is kurtosis?

A

A measure of peak and flatness, or steep and shallowness

46
Q

What is leptokurtic kurtosis?

A
  • high peak
  • suggests low SD
47
Q

What is platykurtic kurtosis?

A
  • flat distribution
  • suggests high SD and variance
48
Q

What have we learned if we experience the ceiling / floor effect?

A

It suggest our sample isn’t representative enough, as otherwise we would have a normal distribution

49
Q

What does it mean if the z-score is positive? Negative?

A

+ above the mean
- below the mean

50
Q

What is a confidence interval?

A

A range of numbers within which we think a population will fall in

51
Q

What is standard error?

A

The standard deviation of the sampling distribution of the mean

52
Q

What is a research / alternative hypothesis? What does it need to include?

A
  • there will be a difference / effect / relationship between the variables being studied
  • needs to be causal or associative
  • needs to be directional or non-directional
53
Q

What is the p value?

A

It is a value that tells you how likely the pattern you have found is down to random chance?

54
Q

What are 3 characteristics of parametric tests?

A
  1. more assumptions about the population
  2. less universal
  3. larger power (can detect effects even in smaller samples)
55
Q

What are 3 characteristics of non-parametric tests?

A
  1. fewer assumptions about the population
  2. more universal
  3. less power (larger samples required to detect an effect)
56
Q

What are the 4 parametric assumptions?

A
  1. the data is interval or ratio
  2. data should be normally distributed
  3. there should be homogeneity of variances
  4. no outliers or extreme scores
57
Q

When do we use t-tests?

A
  • comparing the difference in means
58
Q

What must you report in a repeated measures t-test?

A
  • sample number, means, standard deviation and standard error
59
Q
A

Part A (5 decks)

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