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alevel psychology aqa > RM 2 data > Flashcards

RM 2 data Flashcards

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1
Q

what is data that exist in categories with a natural order.

it gets ranked

A

ordinal data

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2
Q

what is ordinal data

A

Data that exist in categories with a natural order, it can be RANKED or ordered

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3
Q

what is nominal data

A

Data that exist in CATEGORIES with no natural order.

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4
Q

what is ratio data

A

Data with number values that can’t go below zero, for which we can tell exactly how much bigger one number is than another.

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5
Q

what is interval data

A

Data with number values that can go below zero, for which we can tell exactly how much bigger one number is than another.

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6
Q

number of cars sold per day is an example of

A

discrete data

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7
Q

blood pressure of people in a company is an example of

A

continuous data

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8
Q

temperature inside an office is an example of

A

continuous data

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9
Q

number of people working in a company is an example of

A

discrete data

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10
Q

shoe size is an example of

A

discrete data

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11
Q

Whether a participant chooses a male or a female person to talk to.

A

discrete

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12
Q

The length of time someone can endure extreme pain

A

continuous

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13
Q

The number of days someone spends in isolation before showing signs of loneliness.

A

discrete

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14
Q

The sum when $2$ dice are rolled.

A

discrete

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15
Q

The diameter of someone’s pupils in different light levels, measured in

A

continuous

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16
Q

what is discrete data

A

Discrete data is quantitative data that’s restricted to just certain numbers.

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17
Q

what is continuous data

A

Continuous data is quantitative data that’s not restricted to certain numbers.

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18
Q

ratio data can either be

A

discrete or continuous

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19
Q

ordinal and nominal data always has a restricted number of

A

values eg alevel grades or eye colour

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20
Q

ordinal data is …. data

A

discrete

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21
Q

nominal data is …. data

A

discrete

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22
Q

interval data can either be

A

continuous or discrete

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23
Q

quantitative data is split into what types

A

nominal
ordinal
interval
ratio

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24
Q

what is primary data

A

info that is observed or collected directly by the researcher for the purpose of the study that is currently being carried out

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25
Q

what is primary data specific too

A

specifically related to the aims/hypothesis of that study

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26
Q

how might primary data be collected

A

questionnaire
interview
observation
experiment
etc

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27
Q

what would primary data collection involve (5)

A

designing the study
gaining ethical approval
piloting the study
recruiting and testing the participants
analysing the data and drawing conclusions

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28
Q

what is good about primary data

A

the data collection is designed so that it fits the aims and hypothesis of the study (it fits the purpose)

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29
Q

what is bad about primary data

A

time consuming
expensive

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30
Q

what is secondary data

A

information that was collected by someone else for a purpose other than the current study

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31
Q

what can secondary data include (how can the data be collected)

A

data collected by the researcher for a different study or data that was collected by another researcher for a different purpose

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32
Q

secondary data can include (examples)

A

government data eg crime stats, mental health admissions

data held by a hospital or another institution

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33
Q

example of secondary data (type of study)

A

review studies conducting meta analysis on such data

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34
Q

positives of secondary data

A

simple
cheap
to access exisisting data
wmt its less time consuming

the data may have already have been subjected to statistical testing which would identify whether it is significant

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35
Q

what is a negative of secondary data

A

the data may not exactly meet the needs of the study

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36
Q

how can quantitative data not be numbers

A

eg yes and no, the researcher will classify the responses into groups and count the number of ps in each group

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37
Q

A table with the categories in the first column and the frequency count for each category in the second column is called a

A

frequency table

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38
Q

advantages of quantitative data

A

numbers are more objective =more accurate conclusions

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39
Q

advantages of qualitative data

A

reflects opinions, impressions of the researcher, more meaningful, provides greater detail and depth, life from the perspective of the individuals, can catch the subtleties

40
Q

if an obs is unstructured what type of data is being collected

A

qualitative

41
Q

how can continuous data be displayed (4)

A

histogram, bar chart, pie chart, scattergraph, frequency polygon

42
Q

how can discrete data be displayed (3)

A

pie chart, bar chart, scattergraph only correlation and ordinal

43
Q

what is the difference between thematic and content analysis

A

you do not quantify/count the frequency of thematic you just have themes

44
Q

example of what thematic analysis can look like/be done on

A

un and semi structured interviews, diary, unstructured obs

45
Q

what can be done in thematic analysis that cant be done with content analysis

A

you can organise the info into a map to show the links between data and the themes

46
Q

how do you carry out content analysis (5)

A

start by examining a SAMPLE of the media, identify and code potential categories into a tally chart, analyse ALL the media, counting the frequency and quantifying the qualitative data, draw conclusions

47
Q

what is content analysis

A

a research tool used to analyse the content of various forms of communication (written, verbal or visual) it indirectly observes the presence of words/themes within the communication

48
Q

example of content analysis

A

to study the sex role stereotyping in tv adverts

49
Q

what does content analysis do

A

analyses qualitative data by converting it into quantitative

50
Q

what are the measures of central tendency

A

mode, median, mean

51
Q

what are the 3 descriptive statistics

A

measures of central tendency measures of dispersion graphs and charts

52
Q

you have to chose which descriptive stat to use based on

A

level of measurement how the data is dispersed eg any outlying values data tables

53
Q

you can only use a descriptive statistic if it suits …………

A

all the sets of data

54
Q

what is the mode

A

the most frequently occurring value

55
Q

what are advantages of using the mode

A

unaffected by one or two extreme scores
can use on nominal data
useful when other measures mare meaningless
represents a figure that is actually in the set

56
Q

with the mode you can use what type of data

A

nominal

57
Q

disadvantages of using the mode

A

there might not be a mode
small changes in the data can radically alter the mode
there isnt always a single value for the mode wmt the mode becomes less useful.
doesnt tell us anything about the other values in the set

58
Q

what is it called when there are 2 modes for a set of data

A

bi-modal

59
Q

what is it called when there are more than 2 modes for a set of data

A

mulit modal, and it isnt used if this is the case

60
Q

what is the median value

A

the middle value when the scores are arranged in ascending or descending order

when there is an even number the two middle values are added and divided by 2

61
Q

what are advantages of using the median

A

unaffected by extreme outlying values

it can be used on data with skewed distributions, skewed meaning it has an outlying value

62
Q

what are disadvantages of using the median

A

it doesnt work as well with small sets of data
ignores most scores so less sensitive than the mean

63
Q

what is the mean

A

the artithmetic average calculated by adding up all of the scores in the set and dividing by the total number of scores in the set

64
Q

advantages of using the mean

A

makes use of all the data in a set therefore it is the most powerful

65
Q

disadvantages of the mean

A

not to be used on skewed data that has one or two anomalies/extreme values as this can give a misleading average = mean is distorted

it is inappropriate to use on ordinal and nominal data

66
Q

which measure of central tendency should you use if you could

A

the mean

67
Q

what measures of central tendency can you use for nominal data

A

mode only

68
Q

what measures of central tendency can you use for ordinal data

A

median
mode

69
Q

what measures of central tendency can you use for interval/ratio data

A

mean
median
mode

70
Q

scattergraphs can only be used for ….. only

A

correlations

71
Q

what are the 3 measures of dispersion

A

range
interquartile range
standard deviation

72
Q

what are measures of dispersion

A

show how spread out the scores are within a set of data

73
Q

a large measure of dispersion shows what

A

that the scores are widely scattered

74
Q

a small measure of dispersion shows what

A

that the scores are closely clustered

75
Q

what is the range and how is it calculated

A

it is the difference between the highest and lowest scores in a set of data

subtract the lowest value from the highest value

76
Q

advantage of the range

A

easy to calculate

77
Q

disadvantage of the range

A

only considers the 2 extreme values so it can be seriously affected by outlying values

doesnt tell us anything about the distribution of scores in the middle of the set

78
Q

what is the interquartile range

A

measures the spread of the scores in the middle 50% of values when they are placed in numerical order

79
Q

how is the interquartile range calculated

A

calculate the median
calculate the mean of the 25% that is closest above and then again for closest below the median
the IQR is the difference between the 2 means

80
Q

advantage of the interquartile range

A

the top and bottom 25% are ignored which gets over the problem of outlying values

81
Q

what is standard deviation

A

measures the average distance of each score away from the mean

done using the formula

82
Q

advantage of using SD

A

this is the most powerful measure of dispersion and it uses all the scores in the set of data in the calculation

can be used to describe the spread od scores in a normal distribution

83
Q

disadvantage of SD

A

it is less effective when there are outlying scores that skew the data

84
Q

comparision of sd and range

A

sd is less distorted by extreme scores

sd takes account for all the “verbal error scores” from the mean

therefore compared to the range it isnt just the difference between the highest verbal error and the lowest verbal error.

85
Q

measures of dispersion can only really be used appropriately on what types of data

A

interval and ratio

86
Q

what are characteristics of normal distribution

A

symmetrical bell shaped curve
mean, median, mode at same midpoint, dispersion either side of the midpoint is consistent and can be expressed as standard deviations

87
Q

on a normal distribution curve, what % of the scores lie between the mean and one sd above OR below

A

34.1%

88
Q

on a normal distribution curve what % of scores lie between one SD above AND below the mean

A

68.2%

89
Q

for a sample of 1000 people the average IQ score was 100 and the SD was 15, what % of people and how many people would have an IQ of between 100 and 115

A

100 to 115 is 15 which is 1 SD
1 SD=34.1%
34.1% of 1000 is 341 people
0.341 x 1000 = 341

90
Q

what is a skewed distribution

A

where scores are not equally distributed around the mean with a number of extreme scores to one side or the other of the mid-score

91
Q

what does a negative skew look like, where are most of the scores bunched

A

the skew (tail/peak) is in a negative direction, most of the scores are bunches towards the right

92
Q

what is different about the mean compared to other MOCTs in a negative skew

A

mean has a lower value than the median and mode as affected by the extreme lower scores to the left

93
Q

what does a positive skew look like, where are most of the scores bunched

A

the skew (tail/peak) is in the positive direction, most of the scores are bunches towards the left

94
Q

what is different about the mean compared to other MOCTs in a positive skew

A

the mean is always higher than the median and mode in a +skew, as the mean is affected by extreme scores to the right

95
Q
A
96
Q
A

alevel psychology aqa (42 decks)

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