Researching society and culture Alan Bradley Week 5 Quantitative methods (2) Alan.Bradley@warwick.ac.uk Alan.Bardely

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

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

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

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’

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.

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)

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?

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.

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

Univariate analysis Usually frequency tables showing the number of instances occurring, and the % of the whole. May include grouped variables:- Age 20 and under 21-30 31-40 41-50 51 and over Why these intervals?

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

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

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

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)

Suggested readings Bryman, A. 2008 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!

Qualitative research - interviews Next week Qualitative research - interviews