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Psychology 1A > experimental design and statistics > Flashcards

experimental design and statistics Flashcards

1
Q

components of a research study

A 
ethics
sampling
statistical analasys
variables
design
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2
Q

variables

A

“If it cannot be measured, it doesn’t exist” (Eysenck..)
• Any characteristic or factor that can vary
• Example: Darley & Latane (1968)
1) Number of bystanders perceived to be present.
2) Helping behaviour
3) How many seconds before helping
• Can refer to non-observable constructs

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3
Q

exam stress example

A

biological effects
physiological effects
environmental effects
psychollgical

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4
Q

measure meant of variables

A

self report- psychological test
physiolgical- brain activity, hormone levels
behaviour- Overt Unobtrusive Archives

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5
Q

social desirability bias

A

answering in question stop keep in line with social expevtations and judgements e.g. people may lie abut how much they smoke/ drink/self harm

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6
Q

populatin

A

all existing members of a grup

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7
Q

sample

A

a small subset of the population

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8
Q

aim of research study

A

to generalise from a sample to the population

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9
Q

Biased sample

A

may white and eyesnck in 1978

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10
Q

convenience sampling

A

e.g. your friends

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11
Q

random sampling

A
  • Where every member of the population has an equal probability of being selected.
  • Random selection of psychology students
  • Stratified random sampling
  • Small representative sample better than large unrepresentative sample
  • Exit polls in elections • Magazine surveys
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12
Q

research design:observational and correlational

A

use of observations and studies to describe and predict behaviour
• Observe behaviour while it occurs
• Descriptive method
• Can test hypotheses

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13
Q

research design:single case studies

A

describe understand and treat individuals behaviour

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14
Q

experimental designs

A

Manipulate a variable and measure it’s effect in a controlled setting, to establish a cause-effect relationship.

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15
Q

Wild boy of Aveyron

A

Case studies of feral children support “critical period”

hypothesis. (Curtiss, 1977)

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16
Q

observational studies: example

A

• Naturalistic observation of chimpanzee (Jane Goodall, 1986)
• Observed them making and using tools
• Falsified previously held view that animals could not use tools.


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17
Q

observer bias

A
  • Expectations of the observer

* Unconscious cues which influence behaviour of participants

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18
Q

ways to overcome observer bias

A

Coding of procedures
• Observers blind to hypotheses
• Several observers, rate consistency

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19
Q

observational studies: reactivity

A

Change behaviour when we know we are being observed.

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20
Q

observational studies; minimising reactivity

A

Use disguised observation
• Get participants used to observer
• Using unobtrusive measures (e.g., archives)

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21
Q

observational studies: example

A

Hoika & Akhtar (2012): Tested whether 2 - 3 year olds produced novel, copied or cued humour with their parents.
• Participants: 47 parent-child pairs.
• Materials: Toys, video camera.
• Procedure: Parents asked to joke with their child for 10 mins in a playroom setting.
• Coding:Children’s behaviourscoded according to type of humour.
• Objectbased, • Label based, • Conceptual.
• Results: 3 year olds used more label/conceptually based humour than 2 year olds

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22
Q

corelational study

A

• Relationship between 2 variables
• Naturally occurring variations in 1 variable related to
naturally occurring variations in another variable. • Correlation as a basis for prediction
• E.g., intelligence & job success, exam results and time spent preparing.

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23
Q

correlation; scatter plot

A

distribution of relationship

strength of relationship

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24
Q

correlational study: advantags

A

allows prediction

allows study of naturally occurring events

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25
Q

correlation: disadvantages

A

cannot establish a cause effect relationship

directionality and the third variable problem

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26
Q

experimental research design

A

either within subjects or between subjects• Investigates effect of an Independent Variable (IV) on a Dependent Variable (DV).
• All other conditions remain constant

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27
Q

independant variable

A

IV must have at least 2 levels

• Comparison between 2 experimental conditions or groups.

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28
Q

between subjects design

A

different subjects take part in each group

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29
Q

between subjects design: Advantages

A
  • Each Participant naive to procedures

* Essential when testing naturally occurring variables (e.g., Gender)

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30
Q

between subjects design: Disadvantages

A
  • Large number of Participants needed

* Differences in conditions may be due to differences between each group.

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31
Q

within subjects design

A

same subjects tested under al experimenrlconditions

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32
Q

within subjects design: Advantages

A
  • Fewer Ps needed

* Solves problem of between group differences

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33
Q

within groups design: disadvantages

A

Order and Practice
effects
• Use counterbalancing

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34
Q

internal validity

A

The degree to which an experiment supports a clear causal
conclusion
• IV causes DV

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35
Q

factors limiting internal validity

A

Confounding variables
• Expectancy effects
• External Validity

36
Q

tconfounding variables

A 
two interrelated variables IV confound, make i hard o tell which one caused the effect on the DV 
exaples
age
education
motivation
memories
37
Q

confounding variables environment spacific

A

ecperimenter
testing
enviroment
aparatus

38
Q

expecations and demand characteristics

A

experimenter expectancy effects

demand characteristics

39
Q

expeimnrwe wxpctancy effets

A

• Subtle and unintentional cues which influence P’s responses. • Example: E smiling when P behaves as expected.

40
Q

demand characteristics

A

P’s know they haven’t been told everything

• Cues participants pick up about the hypotheses which influence behaviour

41
Q

placeo effect

A

• A substance with no
pharmacological effect • Placebo effect
• Change in behaviour/symptoms due to expectations
• Influenced by colour of pill, packaging, knowledge of practitioner

42
Q

placeboeffect: example homeopathy

A
  • Placebo trials comparing sugar pill with homeopathic pills
  • Results show an improvement in both conditions.
  • Reassurance
  • Culture
43
Q

double blind studies

A

P’s and experimenter kept blind to the experimental condition.
• Minimises placebo effect and experimenter expectancy effects
• Example
• Subliminal learning tapes
(Greenwald et al., 1991)
• Improvements corresponded to label on tape, not contents.

44
Q

external validity

A
  • Can we generalise findings of one experiment to other people and environments?
  • Replication
  • Meta-analysis: combining the results of several studies
  • Bystander effect replicated in different populations (Latane & Herrou, 1996) and in a variety of situations (Fischer et al., 2011).
45
Q

descriptive statistics

A

Describe a set of data using specific measure

• Summarises and describes characteristics of data

46
Q

inferential statistics

A

Allow us to make inferences about a population based on findings
from a sample.
• Statistical significance: unlikely findings would occur by chance alone.

47
Q

bobo doll experiment

A
  • Bandura, Ross & Ross (1961)
  • Children observe adult with Bobo-doll
  • Aggressive behaviour recorded
  • IV=Observation Group (Aggressive/non- Aggressive
  • DV=Number of aggressive acts.
48
Q

measures of central tendency

A

mode is the most common score and mean is sum of results divided y how may results there is
median is the point a which 50% of the scores fall

49
Q

standatd deviation

A

square root of x-xbar all squared over n-1

50
Q

normal distribution the bgger picture

A

Bell shaped curve
• Defined by the mean
and standard deviation
• Example: I.Q of a large sample of the population.
• We can make inferences about a sample if it has a normal distribution.

51
Q

ow do we decide the level of probability to accept or reject the null ypoothesis

A

If there is a less than 5% probability the results are due to error, we reject the Null Hypotheses & infer that the Experimental Hypothesis is correct.
• Expressed as p<.05

52
Q

t test

A

• Comparing differences
between two samples or conditions to calculate a t-value.
• Based on the probability of this value we can then make a decision about whether to retain or reject the null hypothesis.

53
Q

tvalue

A

• t value is a ratio of:
• t= difference between means
variability about the means • t-value large
• the difference in means is large and the variability within the groups is low
• t-value decreases
• As differences in means decrease, or variability increases

54
Q

ttest: low variability sample

A 
andura et al., (1961) 18
IV: ObservationGroup
• Aggressive Male (AM)
• Non Aggressive Male
(NAM)
DV: Number of Punches to
Bobo Doll
55
Q

ttest: high variability sample

A
  • As the Variability (SD) increases, the t value decreases.

* Are these differences in the means significant?

56
Q

testing hypothesis using t tests

A

Using a t-distribution (or statistical software) we can obtain the probability of a t value occurring.
• If the p value is <.05, we can reject the null hypothesis.
• Significant result cannot “prove” a hypothesis.

57
Q

an indépendant sample ttest

A

An Independent Samples t-test is a parametric test which compares means from two separate samples/groups.

58
Q

indépendant ttest: example low validity sample

A 
Example: LowVariabilitySample
Bandura et al., (1961) 18
IV: ObservationGroup
• Aggressive Male (AM)
• Non Aggressive Male
(NAM)
DV: Number of Punches to Bobo Doll
59
Q

high validity sample example

A
  • As the Variability (SD) increases, the t value decreases.

* Are these differences in the means significant?

60
Q

parametric tests

A

make assumptions about data

61
Q

nonparametric tests

A

do no make assumptions about data

62
Q

use t test when

A

making a comparison

63
Q

use correlation wehn

A

looking at relationship between iv and dv

64
Q

paired t test

A

A paired t-test is a parametric test which compares means from the same sample tested under two different conditions

65
Q

assumptions of parametric t tests about data

A

normal distribution
homogeneity of variance
interval/ratio scale

66
Q

non parametric tests

A

Less powerful
• Data that does not meet assumptions of parametric test
not interval radio scale
not normal distraction

67
Q

mann whitney U test

A
  • Scores from each group are combined and ranked from lowest to highest.
  • Does one group have consistently lower ranked scores than the other?
  • Calculate a U value
68
Q

Wilcoxon signed ranks test

A

Calculate difference between each pair of scores
• Difference scores are ranked from lowest to highest.
• Add together ranks of positive scores and of negative scores.
• The smallest value of the summed ranks = T value.

69
Q

why do we need scientific methods

A

• Beliefs, Intuitions, Feelings influence how we explain the behaviour of other people.
• Is our personal (naive) approach valid?
1. Risk of confirmation bias : Only accounting for evidence that
supports our beliefs
2. Hindsight (explainingbehaviouraftertheevent)

70
Q

example: confirmation bias

A
  • Astrologists argue that levels of extroversion and neuroticism are influenced by star sign.
  • Odd numbered signs = tendency to Extraversion
  • Even numbered signs = tendency to Introversion
  • Water signs=tendency to Neuroticism
  • Belief in astrology may have affected results • Eysenck & Nias (1988)
  • Retested children and adults with no knowledge
  • No effect of star sign on personality
  • Example of Confirmation Bias due to belief in astrology
71
Q

hypothesis testing

A

• Darley & Latane (1968)
• Created an emergency situation in a controlled
setting
• Manipulated the number of perceived bystanders
• Measured helping behaviour

72
Q

ethical values i research

A
  • Respect
  • Scientific Value
  • Social Responsibility
  • Maximise Benefit and Minimise Harm
73
Q

zero correlation

A

variables c and y are not related statistically therefore there is no relationship between the two

74
Q

second stage in a research study

A

gather information and form a hypothesis

75
Q

fourth step in the scientific process

A

analyse data draw a tentative and report the findings

76
Q

informed consent involves

A

informing participants of the risks, benefits and procedures of a study

77
Q

third step in the scientific process

A

test a hyspothesis in an ecperiment

78
Q

first step in the scientific process

A

observe something and ask why

79
Q

three essential characteristics of an ecperiment

A

researcher measures effect over one variable
one of more variables re controlled
extraneous factors are controlled

80
Q

the bidirectinality problem

A

being unable to determine a cause effectrealationship

81
Q

in determning a cause effect relaitonship

A

an experiment is an effective tool

82
Q

confounding of variables is …

A

hen two variables are intertwined in such a way its hard to tell which one has actuallyy effect the dependant variable

83
Q

the limitations of hindsight

A

there is no definite way to know which one of the explanations is correct

past events can usually be explained in more than noe way

84
Q

generalisability

A

can information found in a study be imposed on the whole population e.g. this can be difficult in a case study

85
Q

disadvantages of a case study

A

there may be lack of objectivity
findings are often not generalisable
its a poor method of determining cause and effect relationship

86
Q

how critical thinking be applied to science and everyday life

A

it enables individuals to debunk false beliefs
it can assist scientists in solving puzzles of mind and behaviour
it encourages the belief that beliefs and emotion can act a psychological blinders

Psychology 1A (14 decks)

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