Sociology lecture 3
Sept. 27 2011
Research Design, Methodology & Methods
at the beginning you have a very broad research interest
– narrow it down to a specific topic
– review literature- find the holes in the literature
– narrow your topic even further
– research question/hypothesis
– research methods
To collect data:
Participant observation, surveys, interviews
To analyze data:
content analysis, statistical analysis for quantitative data, narrative analysis for qualitative data.
*there are also researchers that also engage in mixed methods. They use from both qualitative and quantitative.
– researchers begin with hypothesis and why questions. (relationships between variables)
– purpose statement: to explain phenomena, to test hypothesis (deductive reasoning)
Scale: Larger sample sizes
methods: surveys, statistical analysis, content analysis
Begins with what & how..
purpose: to explore phenomena (inductive reasoning)
Engages in in depth reasoning . Begins with methods and purpose statements
scale: smaller sample sizes
– involves active participation in the daily life activities of those he or she is observing. It is qualitative in nature. uses processes
of induction as opposed to deduction
– Covert: those in the field are not informed of the researchers status
– semi covert: only some people involved are aware
– open: everyone is aware of the researchers status
“Any systematic procedure which is devised to examine the content of recorded information”
Media Analyzed- Newspapers, books, pamphlets, graffiti, film, tv ect.
Content analysis procedures:
determines research problem, determine unit of analysis, secure the material, specify units of analysis, conduct analysis: Reading &
coding, analyze results
Quantitative methods: Key Concepts
In quantitative research one begins with a testable theory
– a tentative statement about a particular relationship that can be tested empirically.
– Variables are used to measure relationships
independent variable- can be varied or manipulated dependant variable- is the reaction (or lack thereof) of the manipulation
operational definition: describes how a variable is measured.
Types of data-
demographic- refers to things like age/income/household aka census data
social environment- characteristics of a neighbourhood/employment pattern
activities- refers to data about consumer habits/leisure use
opinions/attitude- what people think/do
Cross sectional- a survey trying to reach a cross section on a very broad poll
longitudinal- a survey that takes place over a long period of time
trend- trying to chart the rise and fall of specific trends
cohort- survey looking at a specific generation and certain demographics
Probability: aka the random sample
– each person in the group has an equal chance of being surveyed
Accidental- when a person asks a random person – there is bias with this sample
purposive- when a researcher is trying to target a specific population
snowball- used when researching a very specific inaccessible sample that is hard to get to.
Example of q