Download Methods of research - Everglades High School

METHODS OF
RESEARCH
Learning objectives
◦ At the end of this chapter, students will be able to
understand:
◦ The difference between primary and secondary data and
between quantitative and qualitative data
◦ The range of different research methods and sources of
data used by sociologists and an assessment of their
strengths and limitations
◦ The stages of research design: deciding on research
strategy; formulating research problems and hypotheses;
sampling and pilot studies; conducting the research;
interpreting the results and reporting the findings
Data
Primary
◦ Primary data is information collected
personally by the research
◦ Includes: questionnaires, interviews,
observational studies
◦ Strengths:
◦ Researcher has complete control over how
data is collected, by whom, and for what
purpose
◦ Researcher designs and carries our their own
research increasing reliability and validity of
data
◦ Weaknesses:
◦ Time-consuming to design and execute
◦ Can be expensive; potentially limited access
to target group: refusal to participate or
death
Secondary
◦ Secondary data is data that already exists
in some form
◦ Includes: government reports and statistics,
personal letters, diaries, research by other
sociologists
◦ Strengths:
◦ Ability to save time and money; can by highly
reliable (official statistics)
◦ Sometimes, it is the ONLY available resource
◦ Useful for historical and comparative purposes
◦ Weaknesses:
◦ Not always produced with sociologists in mind
◦ Can be unreliable or reflecting narrow views
rather than wider opinions
Quantitative
Data
◦ Expressed:
◦ Raw number, percentage, rate
◦ Strengths:
◦ Kruger (2003): data allows us to summarize vast
sources of information and make comparisons
across categories over time (EXAMPLES?)
◦ Correlation can test whether hypotheses are
true or false; track changes in a longitudinal
study
◦ Weaknesses:
◦ Artificial environments
◦ Captures narrow range of information—Day
(1998): who, what, when, and where of
people's behaviour
◦ McCullough (1988) suggests issues are only
measured if they are known prior to the
beginning of research
Qualitative
◦ Explores the "why" rather than the "what,
when, where"
◦ Used to understand meanings applied to
behaviour; quality of behaviour
◦ Strengths:
◦ Greater freedom to study people in their normal
settings
◦ Matveev: researchers gain a more realistic feel
of the world that cannot be experienced
through numerical data and statistical analysis
◦ Limitations:
◦ Small group study—limits opportunity to apply
data widely
◦ Difficult to compare across time and location
because groups will never be the same
METHODS OF
SOURCES OF DATA
Primary Methods
Quantitative
Qualitative
◦ Questionnaires
◦ Semi-structured interviews
◦ Structured interviews
◦ Unstructured interviews
◦ Content analysis
◦ Non-participant observation
◦ Experiments
◦ Participant observation
◦ Laboratory experiments
◦ Case studies
◦ Field/natural experiments
◦ Semiology
◦ Cross-sectional surveys
Secondary Methods
Quantitative
◦ Official statistics
Qualitative
◦ Documentary sources
RESEARCH DESIGN
Designing Research
◦ Oberg (1999) says there are four interconnected stages of research design:
◦ Planning is where the researcher decides on the strategy and formulates research
hypotheses or questions
◦ Information gathering involves identifying a sample to study, conducting an initial pilot study
and applying research methods to collect data
◦ Information processing relates to the idea that once data has been gathered, its meaning
must be analysed and interpreted
◦ Evaluation involves both an internal analysis that asks questions about how the research was
conducted and an external analysis, whereby conclusions are reported to a wider public
audience for analysis and criticism
The research problem
Research hypothesis or question
Collecting data (sampling)
Data analysis
Presenting completed research
Sampling
◦ Sampling is a relatively small proportion of people who belong to the target population
◦ Must accurately reflect target population
◦ Sampling Techniques:
◦ Simple random sampling—similar to a lottery; based on probability that random drawing
will produce representative sample
◦ Systematic sampling—taking a sample from the sampling frame
◦ Stratified random sampling—dividing the target populations into groups with known
characteristics
◦ Stratified quota sampling—not everyone in target population has a chance to be
picked
◦ Non-representative sampling—used to understand a particular group in depth
◦ Opportunity sampling—choosing a sample that gives the best opportunity to test a
hypothesis
◦ Pilot study—mini-version of a full-scale study to test feasibility
Completing the Research
◦ Foucault (1970) says data “can never speak for itself;” therefore, it must always be
analysed and interpreted after collection
◦ Analysis and Interpretation:
◦ Internal analysis to ensure data is logical/consistent
◦ Practical analysis relating to the purpose of doing something with the data
◦ External analysis relating to the idea that all research represents the outcome of a
process of social construction
◦ Glaser and Strauss (1967) suggest the final stage of the design process involves four related
elements:
◦ Analysing related research to discover common themes and trends in data
◦ Reflecting on research itself-does it support or disprove the hypothesis?
◦ It is possible to discover patterns in the data?
◦ Does the researcher suggest ways the data can be linked to create an overall theory?