Data handling and analysis

Question 1

What are the 4 types of data?

Answer 1

Qualitative
Quantitative
Primary
Secondary

Question 2

What is qualitative data?

What is quantitative data?

Answer 2

Qualitative data is non-numerical language-based data collected through interviews, open questions and content analysis. It allows researchers to develop insights into the nature of subjective experiences, opinions and feelings.

Quantitative Data is data that is in numerical form (numbers and figures).

Question 3

What are the strengths and weakness of quantitative and qualitative data?

Answer 3

+ Can be replicated.
- Researcher imposition- leading questions- cant gain a true picture of society- low validity.
+ Can help researchers conduct statistical tests with the data.

+ In-depth data provides a bigger picture.
- Researcher bias.

Question 4

What is primary data?

What is secondary data?

Answer 4

Primary data refers to the first-hand data gathered by the researcher himself.

Secondary data means data collected by an organisation. Surveys, observations, experiments, questionnaires, personal interviews, etc. Government publications, websites, books, journal articles, internal records etc.

Question 5

What are the strengths and weakness of primary and secondary data?

Answer 5

+ Reliable due to standardised procedures.
- Bias.

+ Free source of data.
- Outdated- lacks historical validity.

Question 6

What is qualitative data?

What is quantitative data?

Answer 6

Quantitative Data is data that is in numerical form (numbers and figures).

Qualitative data is non-numerical language-based data collected through interviews, open questions and content analysis. It allows researchers to develop insights into the nature of subjective experiences, opinions and feelings.

Question 7

What is a meta-analysis?

Answer 7

A meta-analysis is where researchers combine the findings from multiple studies to draw an overall conclusion. e.g. Van Ijzendoorn and Kronnenberg (1988)

Question 8

What are advantages and disadvantages of meta-analysis’?

Answer 8

+ Meta-analyses draw conclusions based on evidence from multiple empirical sources. Therefore, there is an increased likelihood that meta-analysis findings will be more valid than independent experimental research that forms a conclusion based on a single study’s findings.
+ Meta-analysis in research has many practical applications in psychology. For example, it can provide a reliable, precise summary of whether an intervention is effective as a treatment method.

• Researchers need to ensure the research studies they are combining into their meta-analysis are reliable and valid, as this can affect the reliability and validity of the meta-analysis.
• The studies included in the meta-analysis will likely use different research designs, raising the question of whether the data is comparable.

Question 9

What is a measure of central tendency?

Answer 9

Tells us where the average is in a set of data. There are 3 main measures of central tendency.

Question 10

What is the mean?

Answer 10

The statistical average. Calculated by adding up all the scores and dividing it by the number of scores.

Question 11

What is the mode?

Answer 11

The most frequent occurring score. Calculated by a frequency count.

Question 12

What is the median?

Answer 12

The central value of a data set. Calculated by putting all data scores in order and finding the middle value.

Question 13

What are the strengths and weaknesses of the mean?

Answer 13

+ The most sensitive measure of central tendency, taking ALL scores into account.
- Can’t be used with nominal data.

Question 14

What are the strengths and weaknesses of the mode?

Answer 14

+ Unaffected by extreme scores, useful for discrete data and can be used with nominal data.
- Can be unrepresentative with extreme scores.
- Doesn’t take all the scores in the data set into consideration.

Question 15

What are the strengths and weaknesses of the median?

Answer 15

+ Unaffected by extreme scores and can be used on ordinal data.
- Only takes into consideration the middle number or two middle numbers. (unrepresentative)

Question 16

What does measures of dispersion tell us?

Answer 16

Describes the spread of the data ( or its variation around a central value)

Question 17

What are two measures of dispersion?

Answer 17

Range
Standard deviation

Question 18

What does standard deviation measure?

Answer 18

Measures how widely spread the values in a set of data are around the mean.

Question 19

The more spread the data us from the mean…

Answer 19

The higher the deviation. More individual differences.

Question 20

What do graphs show us?

Answer 20

Provide a visual representation of data findings that make them very accessible and easy to understand by the reader.

Question 21

What are the rules of graphical display?

Answer 21

Must clearly show the findings from the study.
Short, formative title.
Graphs should have both axis clearly labelled (x axis=IV, y axis= frequency).
Always on squared paper.

Question 22

What are bar charts?

Answer 22

A graph in which bars of varying height with spaces between them are used to display data for variables defined by qualities or categories. Bar chart data is discrete as the units measured can’t be split up.

Question 23

What is a histogram?

Answer 23

A histogram is used to portray the (grouped) frequency distribution of a variable at the interval or ratio level of measurement. It consists of vertical bars drawn above scores (or score intervals) so that. The height of the bar corresponds to the frequency.

Question 24

What is a line graph?

Answer 24

A graph in which data points representing a series of individual measurements are shown connected by straight line segments. Line graphs often are used to show trends over time, such as population growth. Also called line chart.

Question 25

What is a scattergram?

Answer 25

A graphical display that shows the relationships or associations between two numerical variables (or co-variables), which are represented as points (or dots) for each pair of score.

Question 26

What is a normal distribution?

Answer 26

Symmetrical, bell-shaped curve. Most people are in the middle area of the curve with very few at the extreme ends. The mean, mode and median all occupy the same mid-point of the curve.

Question 27

What is a skewed distribution?

Answer 27

Distributions lean to one side or the other because most people are either at the lower or upper end of the distribution.

Question 28

What is a positive skew?

What is a negative skew?

Answer 28

• Most of the distribution is concentrated towards the left of the graph, resulting in a long tail on the right.
• Most of the distribution is concentrated towards the right of the graph, resulting in a long tail on the left.

Question 29

What are the levels of measurement (NOIR)

Answer 29

• Nominal: Data is in separate categories.
• Ordinal: Data is ordered in some format.
• Interval: There are equal intervals between each data point.
• Ratio: There is an absolute zero point- no value below zero.

Question 30

What is a correlation?

Answer 30

No manipulation of variables and so cause and effect cannot be demonstrated. The influence of IVs is not controlled.

Question 31

What is an association?

Answer 31

Correlations illustrate the strength and direction of an association between two co-variables.

They are plotted on a scattergram.

Question 32

What are the 3 types of correlations?

Answer 32

• Positive
• Negative
• Zero

Question 33

What is a positive correlation?

What is a negative correlation?

What is a zero correlation?

Answer 33

Positive: as one variable increases, the other increases

Negative: as one variable decreases, the other decreases

Zero: No relationship between the two variables

Question 34

A03 of correlation:

Answer 34

+ Useful starting point for research.
+ Relatively economical.
- No cause and effect.
- The method used to measure variables may be flawed.

Question 35

What is content analysis?

Answer 35

A research technique that enables the indirect study of behaviour by examining communications that people produce.

Question 36

What is the purpose of content analysis?

Answer 36

• A method that analyses qualitative data.
• In its most common form, it’s a technique that allows the researcher to take quantitative data.
• Is usually carried out on secondary data.
• Coding is the initial stage.
• The information must be organised into meaningful units.

Question 37

What is the process of content analysis?

Answer 37

• Research questions
• First, we decide what categories to use.
• Then we can count up the number in each category.
• Next, we study the source and place the characters in it into categories we decided.

Question 38

How to conduct a content analysis?

Answer 38

The process involved in conducting a content analysis is similar to any observational study

But instead of observing actual people, a researcher makes observations indirectly through artefacts that people have produced such as books, films and advertisements

The researcher must make design decisions about…
* The sampling method
* Coding the data
* Method of representing data

Question 39

What is the coding of the data in content analysis?

Answer 39

Coding is the process of placing quantitative and qualitative data into categories

To code data, the researcher must use behavioural categories

For example, if the researcher wishes to look at the way men and women are portrayed in TV programmes, they create a list of behavioural categories and then count the instances of such behaviours in the programme

Decisions about behavioural categories may involve thematic analysis

Question 40

What is the method of representing data in content analysis?

Answer 40

Data can be recorded in each behavioural category in two different ways…

A researcher can conduct a quantitative analysis by counting the instances of each category.
A researcher can conduct a qualitative analysis by describing examples in each category.

Question 41

What are advantages of content analysis?

Answer 41

• Ethical issues are minimised – much secondary data for analysis is available to the public.
• Flexible – can produce quantitative or qualitative data.
• With clear categories, we can test reliability using other researchers (inter-rater reliability).
• Content analysis tends to have high ecological validity because it is based on observations of what people actually do, it involves observing real communications that are current and relevant such as recent newspapers or the books that people read.

Question 42

What are the disadvantages of content analysis?

Answer 42

• Studying out of context: People are studied in directly as part of content analysis outside of contacts within which may attribute opinions and attitudes to the speaker.
• Researcher biased – may suffer from lack of objectivity.

Question 43

What is thematic analysis?

Answer 43

A technique used in content analysis when analysing and summarising qualitative data.

Repeated themes or categories in the material are identified to be analysed and the data is then organised according to these themes.

The material to be analysed might be a book, TV advertisement or the transcript from interviews.

Question 44

What are the main intentions of thematic analysis?

Answer 44

To impose some kind of order on the data.

To ensure that the order represents the participant’s perspective.

To ensure that this order emerges from the data rather than any preconceptions.

To summarise the data so that huge amounts of text or video footage can be reduced.

To enable themes to be identified and general conclusions to be drawn.

Question 45

How do you conduct a thematic analysis?

Answer 45

1. Read and reread the data transcript dispassionately, trying to understand the meaning communicated and the perspective of the participants.
2. Break the data into meaningful units (e.g. sentences or phrases that are independently able to convey meaning).
3. Assign a label or code to each unit, these labels represent the initial categories to be used.
4. Combine simple codes into larger themes, and then instances can be counted or examples provided.
5. Check the emerging categories by collecting a new set of data relating to the topic and applying the categories to this, if the chosen themes are appropriate they should apply to the new data too

Question 46

What are the 6 phases of thematic analysis?

Answer 46

1. Familiarisation with the data.
2. Coding.
3. Searching for themes.
4. Reviewing themes.
5. Defining and naming themes.
6. Writing up.

Question 47

A03 of thematic analysis?

Answer 47

Thematic analysis is a very lengthy process because identifying recurring themes can take a long time, every item needs to be carefully considered and the data needs to be gone through repeatedly.

Quantitative data can be readily summarised with measures of central tendency and dispersion, none of these options is possible with purely descriptive data but thematic analysis allows qualitative data to be analysed and summarised by identifying repeated themes in the material to be analysed.