1. Researching society and culture Alan Bradley
Week 5 Quantitative methods (2)
Alan.Bardely

2. Lecture Outline A brief recap of some terms from last week
Types of quantitative research
Surveys and questionnaires
Samples and pilot studies
Measuring concepts and indicators
Analysing quantitative data

3. Some terms from last week
1) Representativeness – relates to sample
2) Replication
3) Validity
Internal:- Are causal relationships valid?
External:- are results generalisable?
4) Reliability – consistency of measures of concept
More on all of this as we go through the lecture

4. Types of quantitative research
1) Primary data – examples are surveys and questionnaires, structured interviews, content analysis.
2) Secondary data – a) collected by other researchers or: b) collected by institutions.
The focus in this lecture will be on surveys/questionnaires

5. The process in surveys/questionnaires
1) Theory and hypothesis
2) Research question(s)
3) Research design – methods etc
4) Choosing sample – issues raised last week
5) Questionnaire – open/closed question, self completed, mail or face to face, interviewers
6) Pilot study
7) Data collection
8) Data analysis
All of this is an ‘ideal type’

6. Sampling and Pilot study
Sample aims to represent the whole population (remember last week)
Pilot study to check that questions can be understood, no ambiguity, tests the design of the research.

7. Measuring concepts
Some concepts relatively easy to measure, eg sex/gender?
Others may be more problematic, eg social class, social mobility, poverty
‘Measurement (of concepts) provides the basis for more precise estimates of the degree of relationship between concepts’
(Bryman, A. 2008: p144)

8. Indicators of concepts
Measures are quantities (eg household income)
Indicators are concepts which allow us to quantify non-quantifiable concepts
That is, indicators are used as if they are concepts.
What indicators may allow us to measure social class, poverty, attitudes?

9. Indicators of social class
Employment status commonly used:
1) Higher management
2) Lower management
3) Intermediate occupations
4) Small employers/self-employed
5) Lower supervisory/lower technical occupations
6) Semi routine occupations
7) Routine occupations
National Statistics Socio-economic Classification
Think what other indicators could be used.

10. Analysing quantitative data
Univariate - frequency tables/central tendency. Example to follow.
Bivariate – eg gender and educational attainment
Multivariate – computer analysis needed
2 and 3 raise issues of correlation versus cause and effect

11. Univariate analysis
Usually frequency tables showing the number of instances occurring, and the % of the whole.
May include grouped variables:-
Age and under
21-30
31-40
41-50
51 and over Why these intervals?

12. Univariate analysis (2)
Measures of central tendency (Averages)
Mean - total divided by number in group
Mode - figure that appears most often
Median – in the middle, ie the same number above as below

13. Example of central tendency
Annual income in £
1) 5,000
2) 7,000
3) 20,000
4) 20,000
5) 30,000
6) 50,000
7) 200,000
Calculate mean, mode and median incomes

14. Answers Mean = 47,430 Mode = 20,000 Median = 20,000
How useful are these?

15. Measures of dispersion
Range in previous example is:-
5,000 to 200,000
Thus, many of the instances vary widely form the average.
Standard deviation measures the average amount of variation from the mean.
Issues of validity etc
Calculations carried out by computer (SPSS)

16. Suggested readings
Bryman, A Chapter 8 (The nature of quantitative research)
and Chapter 14, just the bit on uni/bivariate analysis
OR:- search in any methods textbook for chapters on quantitative data collection and analysis!

17. Qualitative research - interviews
Next week
Qualitative research - interviews