Research Methods Flashcards

1
Q

correlation

A

a measure of how strongly 2 or more variables are related to each other

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2
Q

is correlation more ethical

A

yes because nothing is manipulated

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3
Q

positive correlation

A

as one variable increases, so does the other

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4
Q

negative correlation

A

as one variable increases the other decreases

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5
Q

correlation coefficient

A

measures the strength of relationship between -1 and +1

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6
Q

2 types of hypothesis

A

null

alternate (one or two-tailed)

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7
Q

two-tailed hypothesis

A

“there is a correlation between”

either positive or negative correlation

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8
Q

one-tailed hypothesis

A

“there is a positive correlation” or “there is a negative correlation”

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9
Q

null hypothesis

A

“there is no correlation between”

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10
Q

nominal data

A

data put into named categories

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11
Q

ordinal data

A

data put into rank order from lowest to highest

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12
Q

interval data

A

data is taken using the same unit of measure throughout the range

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13
Q

discrete data

A

data that can only take a certain individual value

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14
Q

continuous data

A

data that can have any number value in a certain range

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15
Q

assumptions of parametric tests

A

populations drawn from should be normally distributed, variances of populations should be equal, at least interval/ratio data, no extreme scores

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16
Q

why non-parametric tests are used

A

when assumptions of parametric tests can’t be fulfilled, when distributions are non-normal

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17
Q

independent variable

A

the factor you change

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18
Q

dependent variable

A

the result when affected by the independent variable

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19
Q

experiments designs

A

independent groups, repeated measures, matched groups, quasi

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20
Q

independent groups

A

when there are groups of different participants being tested by the same test

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21
Q

repeated measures

A

the groups of participants are the same but given different tests

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22
Q

matched groups

A

the different groups are matched for intelligence/ability/skill etc.

23
Q

quasi

A

an experiment with independent variables that are not open to manipulation therefore, have naturally occurring groups

24
Q

if the standard deviation is large

A

the values are widely distributed and scores can occur a long way from the mean

25
symmetrical distribution
mean = mode = median
26
positive skew
histogram leans to left | mode < median < mean
27
negative skew
histogram leans to right | mean < median < mode
28
central tendency and spread most suitable for skewed distributions
median as mean would be affected by skewed value, IQR for spread
29
central tendency and spread most suitable for symmetrical distributions
mean, standard deviation for spread
30
most suitable graph to show how data is distributed
histogram
31
symmetrical distributions on a boxplot
median in center, whiskers equal length | UQ - median = median - LQ
32
negative skew on boxplot
median closer to UQ | UQ - median < median - LQ
33
type 1 error
when you accept hypothesis but null hypothesis is correct
34
type 2 error
when you accept null hypothesis when hypothesis is correct
35
how to minimise type 1 and 2 errors
ensuring experiments are controlled, reliable and valid
36
descriptive statistics
tables, graphs, mode/median/mean
37
measures of dispersion
variance: average of the squared differences from the mean range: spread of scores standard deviation: a measure of how spread out the scores are (square root of variance)
38
measures of central tendency
mean, mode, median
39
standard deviation
measures the spread of the set of numbers (average of each number from mean)
40
the bigger the standard deviation
the bigger the spread of numbers
41
sample techniques
opportunity, random, self-select/volunteer, snowball, clinical
42
purpose of binominal sign test
difference between 2 conditions when data falls into 2 categories
43
alternate hypothesis
predicts there will be a relationship between the variables and the results are significant
44
target population
the group of people the researcher is interested in and draws the sample from
45
random sampling
each member of the target population has an equal chance of being chose so no bias and likely to be representative but no control over who is selected
46
snowball sampling
relies on initial participants recruiting others to generate additional participants, sample is unlikely representative but easy if specific sample features required
47
opportunity sampling
selecting people most easily available at the time of study, unlikely representative but quick and easy
48
self-selected sampling
people asked to volunteer in the study, unlikely representative but those are usually willing and cooperative so perform best to ability
49
what do you put into the abstract
brief statement of the topic investigated, design used, participants, stimulus materials, apparatus, brief results/analysis/conclusions
50
what do you put into the introduction
review of background material, outline of the topics being investigated, aim and hypotheses
51
what do you put into the discussion
interpretation and meanings of results, limitations of the study, short statement of results, account/explanation of findings, how it has benefited the community and improved understanding
52
what do you put into a harvard reference
surname, first initials, year published, title, book, pages
53
what do you put into the appendices
raw data, statistical calculations, stimulus material, standardised instructions, copies of questionnaires etc
54
what is the purpose of a peer review
to validate new knowledge and ensure integrity, researchers comment on work, follow it up, produce further research