Bryman’s Social Research Methods
Chapter Summaries
Week 1
Chapter 3: Research Designs
Research design : Framework for the collection and analyses of data
- It expresses our priorities in the research
- Experimental, cross sectional, case study
- Longitudinal or comparative
Research method : Technique for collecting data
Variable : An attribute on which cases vary
- Variable different than constant
- Independent vs dependent
Reliability : Are the measures consistent
Validity : Integrity of conclusions
- Measurement validity
- Internal validity
- External validity
- Ecological validity
Classical experiment : Manipulate the independent variable to determine whether it influenced the
dependent variable
- Control group + experimental group
- Internal validity threats : History, testing, instrumentation, mortality, maturation, selection,
ambiguity
- External validity threats: interaction, reactive effects
Evaluation research : Evaluating the effects of occurrences such as social and organizational
programmers
Experimental design
1. Cross sectional : Collecting data on a sample at a single point in time
2. Case study : Detailed and intensive analysis of a single case
o Critical : use to determine the cause and consequences of an event, use to question a
universal assertion/belief
o Extreme, unique
o Exemplifying
o Revelatory
o Longitudinal
, 3. Comparative : Study two contrasting cases using same methods
o Qualitative research
o Multiple case study
Quantitative Qualitative
Cross secional One sample, one time Qualitative content analysis
Case study One case Ethnography on one case
Comparative Comparisons between cases Qualitative comparing cases
Longitudinal One sample at different times Ethnography research, long term
Week 2
Chapter 7: The nature of quantitative research
Quantitative research : Research strategy involving the collection of numerical data
- Deductive
- Positivism
- Objectivist conception of social reality
Main method of data collection
- Questionnaires, surveys
- Quantitative content analysis
- Secondary data analysis
- Structured observation
- Multi method research
Technological innovation
- Self completion questionnaire
- Big data analysis
Preoccupations
1. Measurement
2. Causality
o Causes
o Dependent and independent variables
o Experimental design : independent variable is manipulated to see the effect on the
dependent one
o Cross sectional design : direction of causal influence is less obvious > internal validity
problems
3. Generalizations : sufficient external validity
4. Replication : reduce the contamination of scientist's biases and values
, Steps in quantitative research
1. Theory
2. Research questions
3. Hypothesis
4. Research design
5. Devise measures of concepts: Operationalization
6. Select research sites
7. Select subjects, respondents
8. Collect data
9. Process data: from info to data
10. Analyse data
11. Finding and conclusion
12. Write up conclusions
Deduction + Induction = Positivism
Hypothesis : Informed speculation based on knowledge of the existing research literature
- Relationship between two or more variables
- Null hypothesis : Hypothesis with two possible answers
Concept : Building blocks of theory, points around which social research is conducted
- Labels we give to elements of the social world that seem to have common features
Why do we measure?
1. Identify fine differences
2. Consiste decide to identify differences
3. Basis for more precise estimations on the degree of relationship between concepts
How do we measure?
1. Devising indicators : Indicator to provide a measure of a concept operational definition
- How to devise indicators
o Questions
o Observation schedule
o Official statistics
o Content analysis
2. Multiple indicator measures
- Likert scale : Multiple indicator of a set of attitude resulting to a particular area, used to measure
intensity or feelings
- Indicator must relate to the different objects
- Internal reliability
Reliability : Consistency of a measure of a concept
1. Stability : A measure is stable over time
2. Internal reliability : Indicators are consistent
Chapter Summaries
Week 1
Chapter 3: Research Designs
Research design : Framework for the collection and analyses of data
- It expresses our priorities in the research
- Experimental, cross sectional, case study
- Longitudinal or comparative
Research method : Technique for collecting data
Variable : An attribute on which cases vary
- Variable different than constant
- Independent vs dependent
Reliability : Are the measures consistent
Validity : Integrity of conclusions
- Measurement validity
- Internal validity
- External validity
- Ecological validity
Classical experiment : Manipulate the independent variable to determine whether it influenced the
dependent variable
- Control group + experimental group
- Internal validity threats : History, testing, instrumentation, mortality, maturation, selection,
ambiguity
- External validity threats: interaction, reactive effects
Evaluation research : Evaluating the effects of occurrences such as social and organizational
programmers
Experimental design
1. Cross sectional : Collecting data on a sample at a single point in time
2. Case study : Detailed and intensive analysis of a single case
o Critical : use to determine the cause and consequences of an event, use to question a
universal assertion/belief
o Extreme, unique
o Exemplifying
o Revelatory
o Longitudinal
, 3. Comparative : Study two contrasting cases using same methods
o Qualitative research
o Multiple case study
Quantitative Qualitative
Cross secional One sample, one time Qualitative content analysis
Case study One case Ethnography on one case
Comparative Comparisons between cases Qualitative comparing cases
Longitudinal One sample at different times Ethnography research, long term
Week 2
Chapter 7: The nature of quantitative research
Quantitative research : Research strategy involving the collection of numerical data
- Deductive
- Positivism
- Objectivist conception of social reality
Main method of data collection
- Questionnaires, surveys
- Quantitative content analysis
- Secondary data analysis
- Structured observation
- Multi method research
Technological innovation
- Self completion questionnaire
- Big data analysis
Preoccupations
1. Measurement
2. Causality
o Causes
o Dependent and independent variables
o Experimental design : independent variable is manipulated to see the effect on the
dependent one
o Cross sectional design : direction of causal influence is less obvious > internal validity
problems
3. Generalizations : sufficient external validity
4. Replication : reduce the contamination of scientist's biases and values
, Steps in quantitative research
1. Theory
2. Research questions
3. Hypothesis
4. Research design
5. Devise measures of concepts: Operationalization
6. Select research sites
7. Select subjects, respondents
8. Collect data
9. Process data: from info to data
10. Analyse data
11. Finding and conclusion
12. Write up conclusions
Deduction + Induction = Positivism
Hypothesis : Informed speculation based on knowledge of the existing research literature
- Relationship between two or more variables
- Null hypothesis : Hypothesis with two possible answers
Concept : Building blocks of theory, points around which social research is conducted
- Labels we give to elements of the social world that seem to have common features
Why do we measure?
1. Identify fine differences
2. Consiste decide to identify differences
3. Basis for more precise estimations on the degree of relationship between concepts
How do we measure?
1. Devising indicators : Indicator to provide a measure of a concept operational definition
- How to devise indicators
o Questions
o Observation schedule
o Official statistics
o Content analysis
2. Multiple indicator measures
- Likert scale : Multiple indicator of a set of attitude resulting to a particular area, used to measure
intensity or feelings
- Indicator must relate to the different objects
- Internal reliability
Reliability : Consistency of a measure of a concept
1. Stability : A measure is stable over time
2. Internal reliability : Indicators are consistent
