QUIZ 2 NOTES – chapters 6, 7
Three factors for identifying a population to sample:
Unit of analysis (individual MPs)
Geographic location (Canada)
Time period (1993-2000)
Advantages of sampling:
Restricted to a certain timeframe
Less data collection/entry
Can provide accurate estimates within set parameters we are interested in the population,
sampling is a means to this end
Representativeness of the sample can be affected by:
Accuracy of the sampling frame
The method by which the sample is chosen
Your sampling frame should minimize any inefficiency/inaccuracy
Sample size: Larger sample sizes represent more accurately than smaller ones. To determine effective
sample size we must look at:
The homogeneity of the sample – how similar a population is in regards to the variable of
interest. More homogenous, lower sample size.
The number of variables to study – the more complex our number of variables and relationships,
the larger a sample size needed. Also, if looking at race specifically we might need to skew our
samples in a way which doesn’t represent percentages in the actual population
The desired degree of accuracy – the researcher can state a margin of error they are willing to
The method of random sampling used – Simple Random Sample, Stratified Sample, Cluster
Simple Random Sampling:
All cases are listed and assigned numbers. Cases are then randomized (through a computer etc.)
until proper sample is found
Less random/accurate version uses even intervals between cases to select sample group
Breaks population into mutually exclusive subgroups and then randomly samples each
MP example could be broken up by party affiliation
Increases homogeneity and reduces sampling error, allows focus on small subgroups
Cluster Sampling: Divide the population into a number of subgroups, then randomly select from these subgroups and
select a few to randomly sample. Sampling error increases with every sample taken, larger sample size
can partially remedy this.
Sampling in Qualitative Research:
It is not possible and also not necessary to sample EVERYONE in order to get accurate findings
3 Common Sampling Methods in Qualitative Research:
Purposive – one of the most common strategies, participants are selected according to pre-
selected relevant criteria. Sample size depends on objectives, as well as time allotted. Often
determined on the basis of “theoretical saturation” – the point where no new info will be added
despite new participants. It is most successful when data review and analysis are done in
conjunction with data collection.
Quota – sometimes considered a type of Purposive sampling. We designate quotas for each
characteristic before selecting participants. This allows a focus on specific groups/issues to help
find relevant information. Once quotas are selected, we find people who fit the criteria until
quota is met.
Snowball – Participants use their social networks to refer the researcher to others who may fit
the criteria to participate in the study. Often used to find and recruit “hidden populations”
What is the difference between Qual. And Quant. Sampling?
Name + Describe 2 types of sampling techniques used in Quantitative research
Qualitative Research Methods:
Elite Interviews – “elite” refers to an individual or group with access to necessary specialized
information. In most cases, the size of this group is very small and hard to access. Random sampling
cannot be used, we must include as many members of the elite sample as possible.
Case Studies – Studying in-depth of a specific individual, program, or event. Can be useful to learn more
about a poorly-understood situation, investigating how an individual or program changes over time. We
cannot be sure it is generalizable, however.
• Introduction - A rational for studying the case & who they are and the riding they represent, etc.
• Data Collection - A description of the data you collected - websites, newspapers, etc. Time
period covered etc.
• Patterns or Themes: A detailed description of the facts related to the case.
• Subsection A - Activities in Riding
• Subsection B - Activities in Parliament
• Subsection C - Activities in Party if applicable
• Subsection D - Non-Politician Activities - Volunteer & Activism
• Discussion - A discussion of the main patterns you found. • Conclusion - A connection to the larger scheme of things (ie all backbencher etc.)
Advantages: Useful for gaining an understanding of physical, social, cultural, economic contexts,
relationships, ideas, norms, events, behaviours, and activities. It also enables researchers to become
familiar with the cultural situation. It can serve as a check against participants’ subjective reporting and
uncover important factors to better understand the research problem. It can help us both understand
data after collection, and formulate questions that will give us better understanding of the phenomenon
Direct observation: can be either covert/overt, note frequencies of behavior (via checklist or otherwise).
Indicators must be clear.
Participant observation: covert/overt, researcher becomes a part of the community. This allows for
better understanding and context.
What to observe? Appearance, verbal behavior/interactions, physical behavior/gestures, personal space,
human traffic, people who stand out
Note: clothing, age, appearance, who speaks to whom, for how long, tone of voice, language used, what
people do, roles, interactions, people who enter, leave, spend time at the site. Identify people who
receive a lot of attention from others.
The major disadvantage for participant observation is that it is time-consuming. Traditionally, researchers
spend at least one year observing.
Use neutral language, be clear, keep response categories mutually exclusive and exhaustive, have all
choices available as a category (other/no/no response, etc.), select the highest reliable level of
measurement, pay attention to question order, minimize defensive reaction
advantages: allows for a greater range of questions, respondent is not limited or biased by preset
responses, may provide answers which lead the researcher into new areas.
disadvantages: many possible answers to any given question, data entry becomes v. difficult, time-
consuming, complicates comparison
advantages: respondents can answer quickly, comparison is easy, data entry is less complex
disadvantages: ask respondents for simple response to a complex issue, may encourage statement of
opinion or knowledge where one does not exist
Intensity measures: when yes/no is not enough, number scales (ie 1-7) can be used. Always include an
neutral category in the middle!