Data Handling and Analysis Flashcards Preview

Psychology research methods > Data Handling and Analysis > Flashcards

Flashcards in Data Handling and Analysis Deck (48):
1

What is quantitative data?

Data occurring in numerical form

2

What is qualitative data?

Data occurring in non-numerical form, expressing meaning, feelings and descriptions

3

What is quantitative data used for?

Behaviour

4

What is qualitative data used for?

Attitudes, opinions and beliefs

5

What is more reliable, qualitative or quantitative data?

Quantitative

6

What is a disadvantage of quantitative data?

Lacks detail

7

What is an advantage of qualitative data?

Rich and detailed

8

Where is qualitative data collected?

In a real life setting

9

Where is quantitative data collected?

In an artificial setting

10

How is qualitative data converted into quantitative data?

Through content analysis

11

What kinds of techniques can be used to collect quantitative data?

Closed question questionnaires, experiments, observations, structured interviews

12

What kind of techniques can be used to collect qualitative data?

Open question questionnaires, unstructured interviews, some experiments in the form of opinions/comments from participants

13

What is primary data?

Data collected specifically towards a research aim that has not been published before

14

What is secondary data?

Data originally collected towards another research aim that has been published before

15

Why is primary data more reliable and valid?

Because it has not been manipulated in any way

16

What is good about secondary data?

It is drawn from several sources so can help to give a clearer insight into a research area that primary data cannot

17

What is a meta-analysis?

A process in which a large number of studies with the same research aim and methods are reviewed together are reviewed together and the combined data is tested by statistical techniques

18

What is content analysis?

A method of quantifying qualitative data through the use of coding units

19

What are 4 examples of coding units used in content analysis?

Character
Word
Theme
Time and Space

20

What are the strengths of content analysis?

Turns qualitative data into quantitative so it can be analysed
Reliable, because coding units are not open to interpretation and so are easy to replicate
Easy to perform because it is cheap and also non-invasive (does not require direct contact with participants

21

What are weaknesses of content analysis?

Does not identify causality, merely describes the data
Not done under controlled conditions

22

What are the 6 steps to thematic analysis?

Familiarisation with the data
Coding
Looking for themes
Reviewing the themes
Defining and naming the themes
Writing up

23

What is familiarisation with the data?

Intensely reading the data to become immersed in its content

24

What is coding?

Looking for features of the data important to answering the research question and generating codes for the features

25

What is looking for themes?

Examining the codes and data to identify patterns of potential meaning (themes)

26

What is reviewing the themes?

Seeing if the themes answer the research question.
Themes are refined which can involve splitting, combining or discarding one

27

What is defining and naming the themes?

Detailed analysis of each theme to give each one an informative name

28

What is writing up?

Combining together all the information gained from the analysis

29

What are the three measures of central tendency?

Mean
Median
Mode

30

What are advantages of the median?

Unaffected by 'freak' scores
Easier to calculate than the mean
Can be used for ordinal data but the mean can't

31

What are disadvantages of the median?

Can be unrepresentative in a small sample
Not as sensitive as the mean because not all the scores are used in the calculation

32

What are advantages of the mean?

Most accurate
Most representative because it uses all the data

33

What are disadvantages of the mean?

Not useful if the scores are skewed e.g. if there are some really large and some really small numbers
May not be one of the actual scores

34

What are advantages of the mode?

Less prone to distortion by 'freak scores'
Sometimes makes more sense than the mean e.g. you can't have 2.1 people

35

What are disadvantages of the mode?

Sometimes you can have more than one mode
Does not use all the scores

36

What are the two measures of dispersion?

Range and standard deviation

37

How do you calculate the range?

Subtract the smallest value from the largest value in a set of data

38

What are the advantages of the range?

Takes into full account the extreme values (uses all the data)
Easy and quick to work out

39

What are the disadvantages of the range?

Affected by 'freak' extreme values
Does not show whether data are clustered or spread evenly about the mean

40

What are advantages of standard deviation?

Measures dispersion
Allows for interpretation of individual scores

41

What are disadvantages of standard deviation?

Harder to calculate
Less meaningful if data are not evenly distributed

42

What can percentage data be plotted on?

A pie chart

43

What is correlation data plotted on?

A scattergraph, which indicates direction of correlation

44

When to use a bar chart and when to use a histogram?

Histograms are generally used for continuous data
Bar charts can be used for nominal data

45

What kind of data does a histogram use?

Continuous

46

Advantage of frequency polygon?

2 or more frequency distributions can be compared on the same graph

47

What is a normal distribution?

Data with an even distribution of scores either side of the mean

48

What is skewed distribution?

Data that does not have an even distribution of scores either side of the mean