data handling an analysis

Question 1

diff bw primary and secondary data

Answer 1

primary data is gathered directly from the PTS and is specific to the aims of the study whereas secondary data has been collected by a third party, not specifically for the aims of study, and then used by the researcher

Question 2

example of primary data

Answer 2

interview recordings

Question 3

example of secondary data

Answer 3

medical records from a hospital

Question 4

diff bw quantitative and qualitative data

Answer 4

quantitative data produces numerical data whilst qual prod opinion based data

Question 5

data collection techniques

Answer 5

quantitative and qualitative

Question 6

strengths of qualitative data

Answer 6

greater external validity
more richness of data
gives more insight into beh

Question 7

weaknesses of qualitative data

Answer 7

difficult to analyse

Question 8

strengths of quantitative data

Answer 8

easy to analyse

Question 9

weaknesses of quantitative data

Answer 9

lose insight of beh

Question 10

meta-analysis

Answer 10

process of combining results from a number of studies on a particular topic to provide an overall view

Question 11

what type of data is analysed using content analysis

Answer 11

qualitative

Question 12

what type of data would PTS written responses to an open question be

Answer 12

qualitative

Question 13

weaknesses of meta analysis

Answer 13

can be prone to publication bias- file drawer problem
researcher may not select all relevant studies-leaving out one w/neg/non-sig res
.: bias as only rep some rel data and incorr concl drawn

Question 14

what type of data does meta analysis use

Answer 14

secondary

Question 15

what type of data would be collected in a structured ob using s checklist

Answer 15

quantitative

Question 16

strengths of primary data

Answer 16

.

Question 17

weakness of primary data

Answer 17

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Question 18

strengths of secondary data

Answer 18

.

Question 19

weaknesses of secondary data

Answer 19

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Question 20

strength of meta analysis

Answer 20

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Question 21

draw normal distribution graph

Answer 21

.

Question 22

draw positively skewed distro

Answer 22

-

Question 23

draw negatively skewed distro

Answer 23

.

Question 24

characteristics of normal distribution

Answer 24

.

Question 25

characteristics of positive skewed distro

Answer 25

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Question 26

chara of negatively skewed distro

Answer 26

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Question 27

correlation coefficient

Answer 27

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Question 28

using an example explain the difference bw a positive an negative skew

Answer 28

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Question 29

when are bar charts an appropriate graphical display

Answer 29

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Question 30

when are scattergrams an appr-appropriate graphical display

Answer 30

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Question 31

when are histograms an appropriate graphical display

Answer 31

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Question 32

descriptive statistics

Answer 32

figures that allow us to describe and summarise data, but don't allow us to make conclusions related to the hypothesis mean, median, mode, range, standard deviation

Question 33

measures of central tendency

Answer 33

averages which give us info about he most typical values in a set of data mean, median, mode

Question 34

measures of dispersion

Answer 34

based on a spread of scores- how far scores differ from one another range, standard deviation

Question 35

mean

Answer 35

arithmetical average, add up scores and divide by total number of scores

Question 36

mode

Answer 36

result that appears most frequent in a set of data

Question 37

median

Answer 37

middle score, order results in ascending order and the middle value is the median

Question 38

evaluate use of mean

Answer 38

most sensitive as uses all values, most representative | easily distorted by extreme values,eg.., dx data overall

Question 39

evaluate use of mode

Answer 39

easy to calculate good for data in categories,eg., by selecting modal group crude measure,can b quite diff from mean and median, not really representative not use full for small sets of data

Question 40

evaluate use of median

Answer 40

unaffected by extreme value unlike mean | ignores v.lagre/ small outliers so not appropriate for nominal data

Question 41

range

Answer 41

simple calc from a spread of scores, subtract lowest value from highest value and (usually) add one

Question 42

why is 1 added when calculating the range

Answer 42

acts as mathematical correction to allow for the fact that raw scores are often rounded down when rec w/in research e.g. 45.4s to 45s

Question 43

evaluate use of range

Answer 43

easy to calculate only takes into account extreme values unlike median, unrep of set of data as a whole may not give fair rep of gen spread, e.g. student given test for hm by mistake scoring almost double comp to rest of class

Question 44

standard deviation

Answer 44

tells us how much scores move away from the mean by calc diff bw mean and each score, sum of diffs divided by n' scores, gives variance, square root of the variance

Question 45

evaluate use of SD

Answer 45

much more precise that range as inlc all values w/in inal calc however, sim to mean, for this reason can be distorted by a single extreme value

Question 46

what does a large sd sug in a particular conditon in an experiment

Answer 46

not all pts aff by iv in same way bc the data are quite widley spread, may be few anomalous resuls

Question 47

what does a large sd sug in a particular condition in an experiment

Answer 47

not all pts aff by iv in same way bc the data are quite widely spread, may be few anomalous results

Question 48

what does a low sd sugg

Answer 48

data tightly clustered around mean

Question 49

what does low sd sugg in particular cond

Answer 49

all pts responded in a fairly similar way

Question 50

explain when is the mean the best option

Answer 50

when there are no extreme scores in the set of data as it is the most sensitive out of the three mocds

Question 51

explain when is it best to use the median

Answer 51

if there is an extreme score as mean would be distorted

Question 52

when is never the best option, what is the exepction

Answer 52

mode, if data are in categories

Question 53

example of meta-analysis

Answer 53

cultural variation in attachment types- van ijzendoorn

Question 54

data analysis

Answer 54

process of turning data in to information by adding context

Question 55

data

Answer 55

collected in investigation in words, numbers, images, sounds. without meaning

Question 56

levels of measurement

Answer 56

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Question 57

nominal

Answer 57

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Question 58

ordinal

Answer 58

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Question 59

interval

Answer 59

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Question 60

inmportant things whn drawing graph or table

Answer 60

title | label axis/ columsn