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PS1002 > Methods and stats > Flashcards

Methods and stats Flashcards

1
Q

what are the four levels of measurement

A

N - nominal
O - ordinal
I - interval
R - ratio

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2
Q

Nominal

  • what type of data
  • what type of stats
A

qualitative data
categorical
named
mode as would tell us which of the categories is the most commonly occurring

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3
Q

Ordinal

  • what type of data
  • what type of stats
A

quantitative
numbers have an ordered relationship
numbers indicate position on a list
eg first, second, third
differences between adjacent scores do not represent equal quantities
the median, range and interquartile range are appropriate as these measurements are based on position

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4
Q

Interval and ratio

  • what type of data
  • what type of stats
A

quantitative
numbers say what they mean - numeric properties are literal
interval as no absolute zero
the mean, standard deviation and standard error are appropriate descriptive stats
ratio as there is an absolute zero

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5
Q

what is parametric data

A
  • The scores (the DV) must be at an interval or ratio scale.
  • The data must be normally distributed.
  • The groups must have homogeneity of variance (similar variances).
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6
Q

what are non-parametric tests

A

tests that make few or no assumptions about the shapes underlying the population distribution
also known as distribution free tests
can be used on low level data such as ranked data
parametric tests often have a non-parametric equivalent

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7
Q

is this test parametric or non-parametric?

chi-squared

A

non-parametric

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8
Q

is this test parametric or non-parametric?

Spearman’s Rho

A

non-parametric

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9
Q

is this test parametric or non-parametric?

paired samples t-test

A

parametric

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10
Q

is this test parametric or non-parametric?

independent samples t-test

A

parametric

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11
Q

is this test parametric or non-parametric?

Wilcoxon T-test

A

non-parametric

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12
Q

is this test parametric or non-parametric?

Mann-whitney U test

A

non-parametric

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13
Q

is this test parametric or non-parametric?

Pearson’s correlation coefficient

A

parametric

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14
Q

pair up the seven tests with their parametric / non-parametric equivalents

A

chi-squared & n/a
Wilcoxon T-test & paired samples t-test
Mann-Whitney U test & independent samples t-test
Spearman’s Rho & Pearson’s correlation coefficient

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15
Q

advantages of non-parametric tests

A

analyses can be simplistic and easier to complete
useful for data on nominal or ordinal scales
can be used with small sample sizes
useful if data violates the assumption of normality
useful if data is severely skewed or has outliers
makes fewer assumption so tests can be more robust

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16
Q

disadvantages of non-parametric tests

A

less powerful, typically only make use of ordinal information only. as such large sample sizes may be needed to find significance
due to having to assign ranks, analyses can be annoying if sample size is very large

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17
Q

utilitarianism
what who
where/ how is it in practice
but…..

A

the greatest happiness principles
Jeremy Bentham (1748-1832)
John Stuart Mill (1806-1873)
hedonic calculus
constrained utilitarianism - human and animal research based on cost-benefit analysis, but with absolute limits defining acceptable practices
but what are the limits of acceptability? who decides?

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18
Q

who are the professional codes of conduct for psych

A

American psychological association
british psychological society
society for neuroscience
world medical association (including BMA) - the declaration of Helsinki

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19
Q

examples of why we should worry about human research

A 
military studies in Nazi Germany
Tulane - heath curing homosexuality
tuskgee syphilis study
zimbardo
milgram and asch social conformity study
the 'unfortunate experiment' NZ
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20
Q

ethics in human research - key points (8)

A 
informed consent
motivation for being a subject
degree of risk or personal harm
right to withdraw
confidentiality - data protection act
protection of participants
debriefing
follow-up procedures to detect and mitigate any lasting adverse effects
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21
Q

who reviews our ethics

A

at university - school ethics committee and UTREC (university teaching and research ethics committee)

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22
Q 
ethics of research on animals - why worry?
key points (5)
A 
invasiveness
behaviour manipulations
field work
housing conditions
genetic manipulations
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23
Q

viewpoints on animal research and their weaknesses

absolute anti-research

A

ethical status of animals = humans
weakness
unreasonable conclusions
removes limits to ‘direct action’, actually requires it
failure to recognise human awareness (Singer)

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24
Q

what is direct action

A

terrorism staff firebombed, kidnapped, threatened with murder

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25
Q

viewpoints on animal research and their weaknesses

absolute pro-research

A

animals as tools, objects
weakness
unreasonable conclusions - kill all dogs for one human? animal ownership rather than stewardship
failure to recognise inherent worth of animals
modelling paradox for human disease - to the extent animals are not like humans, then they are poor models. to the extent that they are like humans, then we should not use them

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26
Q

animal research in the UK

2007

A

3.2 million procedures

by comparison 10 million cats in the UK kill 300 million animals and 2.5 billion fish and animals are consumed in the UK

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27
Q

ethical conduct of research key point (5)

A 
plagiarism
intellectual honesty and data analysis
determining authorship
conflicts of interest
relationship with the media
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28
Q

what does Wilcoxon T-test do

A

establish if there is a change from one condition to the next

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29
Q

Wilcoxon T-test

what type of data

A

non-parametric (is the equivalent of paired samples t-test)

data must be at the ordinal scale or higher

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30
Q

what does the Wilcoxon T-test tell us

A

gives us information about the direction and magnitude of the difference between pairs of scores

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31
Q

steps in carrying out Wilcoxon T-test

A
  1. First describe the two data sets by calculating the median or mean (this depends on the type of data you have collected - for ordinal data use the median and for interval or ratio data use the mean)
  2. Calculate the difference between the two conditions (D = X1 – X2).
  3. Assign ranks to these differences ignoring the plus and minus signs and omitting any pairs of scores with a difference score of zero.
  4. Add back in the plus and minus signs to each rank. Add up the ranks with plus signs and then add up the ranks with minus signs. The smaller of these two values is your T value.
  5. Look up the critical value in the table (p.66) according to your N (omitting pairs of scores with a difference score of zero). If your T value is EQUAL TO OR LESS THAN the critical value you have significance.
  6. Report your Wilcoxon statistic as: T(n) = X, n.s. OR T(n) = X, p<0.05
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32
Q

what are the two types of Chi-squared

A

goodness of fit - deals with nominal data (so data is categorized)
test of association - two or more groups

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33
Q

Chi-squared goodness of fit - info

A

examines one nominal variable and looks at how participants are allocated to different categories within that variable
deals with frequency of scores in each category
categories must be mutually exclusive - independent
we are looking at the distribution of observed frequencies compared to expected frequencies
how good is the fit between the observed and expected frequencies
there are two possible null hypotheses

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34
Q

Chi-square goodness of fit hypotheses

A

null hypotheses
in general: that there is no difference between the distribution of our observed frequencies and the expected frequencies
1 - the population is evenly distributed across the categories (as you would expect by chance). there is no preference for one category over another
2 - the proportions in each category do not differ from a comparison population that has published expected frequencies
alternative hypothesis - there is a difference between the distribution of our observed frequencies and the expected frequencies - no specific prediction so two-tailed

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35
Q

how to carry out Chi-squared goodness of fit

A

draw a contingency table (table with categories, observed and expected frequencies)
1 - calculate expected frequencies
2 - record observed frequencies
3 - calculate Chi-squared
4 - check significance with degrees of freedom
5 - interpret results

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36
Q

degrees of freedom in Chi-squared goodness of fit

A

= number of categories - 1

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37
Q

when to use Chi-squared test of association

A

two nominal variables and want to know if they are associated

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38
Q

hypotheses in Chi-squared test of association

A

null - that two nominal variables are not associated (two nominal variables are independent
alternative hypothesis - that two nominal variables are associated

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39
Q

steps in how to do Chi-squared test of association

A 
1 - create contingency table
2 - record observed frequencies
3 - calculate expected frequencies (row total x column total divided by total
4 - calculate chi-square
5 - check significance
6 - interpret results
40
Q

degrees of freedom in chi-square test of association

A

(r-1)x(c-1)

41
Q

what is reliability and 3 subsections

A

the extent to which a measurement is repeatable and consistent
- internal consistency
2 - inter-rater reliability
3 - test-retest

42
Q

what is internal consistency

A

the extent to which tests or parts of tests asses the same characteristic, skill or quality
a measure of reliability of different test items intended to measure the same characteristic
internal consistency reflects the extent to which items of a test measure various aspects of the same characteristic and nothing else

43
Q

what is inter-rater reliability

A

after observing the same behaviour, the recordings of two or more researchers should match
“calibrating” the observers
inter-rater reliability is dependent upon the ability of two or individuals to be consistent
training, education and monitoring skills can enhance inter-rater reliability

44
Q

test-retest

A

consistency of a measure from one time to another
when an individual sits the same test multiple times, they should get the same result each time
the most popular indicator of reliability, quantified by correlation coefficient measurement

45
Q

what is validity

3 subsections

A

the extent to which a test measures what it claims to measure

  • construct validity
  • external validity
  • internal validity
46
Q

construct validity

A

whether a scale measures the theorized psychological construct that it purports to measure

47
Q

external validity

A

the degree to which the conclusions in your study would hold for other persons in other places and at other times
population validity - whether the sample represented the entire population
ecological validity - how well methods, materials and setting of the study approximate the real-life situation

48
Q

internal validity

A

feeling confident you can make causal statements about what happened in your study
the independent variable causes the change in the dependent variable
your study is free of confounding variables

49
Q

explain the trade off between internal and external validity

A

a tightly controlled experiment is likely to have strong internal validity but results will be harder to generalize
more naturalistic research will have better external validity, but will be poorer in terms of control and subsequent internal validity

50
Q

name the eight threats to internal validity

A 
selection
maturation
history
repeated testing
instrumentation
experimental mortality
selection-maturation
experimenter bias
51
Q

selection

A

differences between groups may exist pre-test that could interact with the independent variable and thus be ‘responsible’ for the observed outcome
aim to have unique individual characteristics evenly distributed between groups (such as sex, ethnicity, attitude etc)

52
Q

maturation

A

participants may change in the course of the experiment or between repeated measure of the dependent variable
some of these changes are permanent such as growth whereas others such as fatigue are temporary

53
Q

history

A

outside events may influence participants in the course of the experiment or between repeated measures of the dependent variable
often these are large scale events that affect participants’ attitudes and behaviours (eg war, natural disaster)

54
Q

repeated testing

A

repeatedly measuring the participants may lead to bias. simply taking the pre-test may affect how participants do on the post-test
1 - participants may become less anxious; they may remember answers; become aware of concepts that weren’t originally known. subject to practice effects.
2 - features of the experimental situation may change from test session 1 to test session 2

55
Q

instrumentation

A

a threat produced by changes in the measurement instrument itself such as changes in calibration of a mechanical measuring device or the proficiency of a human observer or interviewer

56
Q

experimental mortality

A

between testing sessions participants may withdraw from the study
there could be differences between those who remain in the study and those who drop out
such as those who are less intelligent tend to drop out

57
Q

selection-maturation

A

participant-related variables and time-related variables may interact
the difference between the groups is always present but only becomes evident through the maturation process
the participants selected into treatment groups may mature at different rates

58
Q

experimenter bias

A

the experimenter intentionally or unintentionally biases the study and therefore influences the outcome
use a double blind study: an experimental procedure in which neither the participants nor the experimenter know the critical aspects of the experiment (who receives placebo and who receives treatment)

59
Q

demand characteristics

A

a feature of the experimental situation that indicates to the participants:
how the researcher would ideally like them to respond in the study
the true purpose of the study
subsequently participants alter how they respond

60
Q

participant reactivity

A

the influence the experimental situation may have on the participant
1 - negativistic participant role
2 - apprehensive participant role
3 - good participant role

61
Q

blind design

A

the participant does not know which condition they are in for the study - reduces demand characteristics

62
Q

double blind

A

neither the participant nor experimenters know who is in the experimental group and who is in the control group - removes both experimenter bias and demand characteristics

63
Q

what is correlation

A

indicated an association between two variable. more specifically the strength and direction of a linear relationship between two variables

64
Q

positive correlation

A

bottom left to top right

as one variable increases, so does the other

65
Q

negative correlation

A

top left to bottom right

two variables moving in opposite direction to each other

66
Q

no correlation

A

as one variable changes, the other variable does nothing

67
Q

how do we visually show correlation

A

scatter graphs

68
Q

the most important thing to remember about correlation

A

correlation does not imply causation

69
Q

how to calculate correlation coefficient

A

• Correlation coefficient = r
• Correlation coefficient varies between -1 and +1
• Direction: sign of value shows ‘-‘ or ‘+’ relationship
• Magnitude: closer to 1 the stronger the relationship (ignoring the sign)
• If r=-1 or +1, a perfect linear relationship exists
• If r=0, there is no linear relationship
• Interpreting r
o O.7-1.00 = strong
o 0.5-0.69 = moderate
o 0.3-0.49 = weak

70
Q

what are the two versions of correlation coefficient and why are there two

A

• Versions of the correlation coefficient
o Parametric: Pearson’s correlation coefficient
o Non-parametric: Spearman’s rho

71
Q

how to carry out Pearson’s correlation coefficient

A

fill in table with x and y squared

plug into formula

72
Q

how to carry out Spearman’s Rho

A

MUST FIRST RANK DATA

then same as pearson’s but with the ranks

73
Q

degree choice and conservatism - do students studying different disciplines differ in their conservatism score background research

A

vocational choice may be a function of personality
we look for jobs that fufil our interests - Super 1957
vocational choice may reflect one’s own life style - Holland 1985
choosing a degree course may share similarities with occupation choice

74
Q

the creation and evolution of the conservatism scale

A

conservatism - a desire to retain traditional social institutions
scale originally developed by Wilson and Patterson 1968 - 50 items
adapted and abbreviated by kirton 1978 - 30 items (scale investigates 3 dimension: religious, sexual and moral control)
abbreviated again Joe 1984 - 20 items
this latest version of the scale has not been standardised, scores from this scale may not be normally distributed

75
Q

what is the Mann-Whitney U test trying to achieve

A

non-parametric test (ordinal data or higher) aimed at answering whether two groups perform differently on a task

76
Q

how to carry out the Mann-Whitney U test

A
  1. Calculate the medians for each group.
  2. Rank scores (combining the groups). Zero values DO count.
  3. Total the ranks for each group separately.
  4. R= largest total of summed ranks. N1 = number of participants in the group that has the largest sum of ranks.
  5. Determine the U value using the equation: U = (N1 x N2) + N1 x (N1 + 1) – R 2 6. Look up the Mann-Whitney U test critical value on the table (p.67-68).
  6. N values in Significance Tables: smaller N value down column, larger N value across the row (if sample sizes are different).
  7. Table gives two ranges of scores. If your U value lies within one of these two ranges your result is significant. 9. U(N1,N2) = X, p<0.05 or U(N1,N2) = X, n.s.
77
Q

dysfunction to neural circuits - name some of them and the psychiatric conditions underlying them
and separately some causes

A

Parkinson’s disease - motor circuits
Major depressive disorder - mood circuits
Alzheimer’s disease - cognitive circuits
damage can be caused by:
-damage to pathways, stroke
-loss of neural elements / populations, Parkinson’s
-disordered firing, epilepsy)

78
Q

why would we carry out deep brain stimulation

A

there are a variety of disfunctions to neural circuits that underlie many symptoms of different psychiatric conditions
so successful treatment of these circuits has come about through stimulating particular circuits (called deep brain stimulation)
benefit was initially found in movement disorders, such as Parkinson’s
in patients that have had conventional therapies without success, DBS has been successful (loranzo and lipsman 2013)

79
Q

how does DBS work

A

Electrodes implanted in specific region of the brain, subject is awake to aid placement
• Electrodes are connected to a programmable pulse generator that is implanted under the skin, below the collarbone
• Can change settings of frequency, pulse width, amplitude to maximise clinical improvement
• Mechanism of how DBS works is currently unknown

80
Q

what are the problems with DBS - not ethical

A

with time and disease progression many symptoms in Parkinson’s disease develop even I those with DBS surgery
does not work for all patients
alleviates some symptoms but not a cure
problems with major surgery such as infection
possible side effects of mood disturbance

81
Q

possibilities for the future with DBS

A

All actions, feelings, thoughts generated in the brain
• Therefore, those with actions, feelings, thoughts that are unacceptable to society (e.g. a pedophile, psychopath) have abnormal brains in some way
• These circuits could be silenced/re-programmed using DBS

82
Q

treatments for spinal cord injury

A

worldwide, over 130000 people each year survive spinal cord injury but sustain extensive paralysis (approx. half of these occur above the sixth vertabra so affecting all four limbs)
most of these patients indicate that regaining the ability to grasp objects would provide the greatest practical benefit compared to regaining other lost functions

83
Q

potential treatment for spinal cord injury

A

brain-machine interface
monkeys implanted with multi-electrode recording array in the hand area of M1
Separate surgery to implant intramuscular electrodes for recording and stimulation of hand and forearm muscles
Normal trials where data acquisition can start to predict the movements signalled by brain
Used neural predictions to control electrical stimulation of muscles having disabled the normal control of these muscles from brain
so could machines effectively replace outputs from the brain from motor cortex or even processing within the brain so frontal lobe?

84
Q

functions of the frontal lobe

A 
decision making
attention
impulsivity
emotions
old memories
personality
85
Q

aims of perception practical

A

does body physique relate to attributions to faces
Xu Lei
masculinity
attractivenessdoes context affect attraction to face cues
what stats
what methods for perceptual tests

86
Q

defining how face shape changes with weight (BMI) - how were images made

A

took averages of 10 high BMI men and 10 low BMI men

87
Q

what is BMI / problem

A

body mass index = fat and muscle

fat and muscle will affect face shape differently

88
Q

fat and muscle predictions for masculinity and hypotheses

A

increased weight makes men look stronger
men have less fat and more muscle than women
hypothesis
increased muscle and fat increases masculinity
high muscle face shape looks more masculine than high fat face shape
muscle will enhance masculinity than fat

89
Q

method for perception practical

A

transform face shape related to muscle and fat to 5 levels of muscle and 5 of fat
present faces
get ratings with a visual analogue scale low to high masculinity

90
Q

what stats were used in the masculinity perception practical

A

calculated average ratings for each participant for 5 levels of fat and musce
tested if +4 transformed more masculine than low -4
carried out Wilcoxon t test

91
Q

what were the results of perception masculinity practical

A

increasing fat and muscle increase masculinity

muscle increases masculinity more than fat

92
Q

attraction perception practical hypotheses

A

choose more muscular (masculine) face for short than long term relationship

93
Q

attraction perception practical method

A

face images - transform fat and muscle

choose most attractive transform level for long term relationship, short term sexual relationship

94
Q

what stats carried out and result for attraction perception practical

A

paired t test
higher cues to muscle preferred for short compared to long term relationships
but higher level of fat cues not preferred for short compared to long term relationships

95
Q

summary of three types of method for perception practical and positives / weaknesses

A

rating
-used for masculinity
-low sensitivity
-shows relative importance of different sues
method of adjustment or interactive choice
-used for attraction
-high sensitivity
-appropriate if optimal level of cue not know
forced choice between 2 alternatives (wasn’t used)
-high sensitivity
-need to know what to compare

96
Q

what does r^2 tell us

A

coefficient of determination
gives a percentage
how much of one factor can be attributed to the other factor

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