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Lecture 3

PSYC 2030 Lecture Notes - Lecture 3: Convenience Sampling, Amazon Mechanical Turk, Participant Observation

Course Code
PSYC 2030
Kerry Kawakami

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Lecture 3
January 20th 2016
Sampling, Measurement, and Naturalistic Observation
Types of Research
- Basic vs Applied
oDifference is basic research is done with no intent to take the study into the real
world. Applied research has connections to the real world
oBasic research: “The more we know about the world, the better”
oApplied research: “How can this be applied elsewhere?”
oUsually, applied research is done to solve a problem, whereas basic research is
done to know more about the world
- Laboratory vs Field
oEx: People’s reaction to horror movies
oField: Sit in a theater and observe people. Ask movie viewers questions before and
after, do cortisol tests etc (people chose to watch the movie on their own) Here, we
get more realism
oEcological Validity: What happens in the study is what happens in the real world,
field research has higher ecological validity
oAdvantages: Participants have no expectations
oDisadvantages: Higher cost
oLab: Bring people into a lab and study people there (perhaps with more control)
(people are not able to chose what movie they want to watch). Lab study usually has
more control over the situation
oAdvantages: Participants are chosen specifically
oIf a study is done in both a lab and field and get opposite results, this is bad because
we don’t learn anything from the lab study. It means the lab study had low ecological
validity. The findings from the lab study correlate with field studies r=.71 (high
oBut, 14% of effects changed sign from lab to field (Studies in lab and field show
opposite results, about 1/7 studies done in both lab and field result in opposite
results) (Studies demonstrating small effects are the ones that usually show
opposite results in lab and field. Ex: gender differences)
-Basic usually happens in a lab, and applied usually happens in the field however this is not
always true
- Qualitative vs Quantitative
oQuantitative: Collect data in the firm of numbers
oQualitative: Collect non-numerical data (Ex: Ask people to write an essay about
oQualitative provides more detailed information about participants. Also, most
researchers turn the qualitative data into quantitative data (numbers)
oDisadvantage of Qualitative: Harder to turn qualitative into quant, there is a potential
for bias when transforming qualitative to quantitative (because the researcher has to
come up with a coding scheme Ex: People send in pictures of how messy their desk
is. How does the researcher determine what is messy and what is not? By the
number of food items on a desk? Or non related work items? etc)
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-Who provides data?
-How many people provide data?
-Who and how many people you ask for data will both affect how your study will go/what kind
of data you will receive
- Population: Is a group of people that we are interested in. Populations can be large or small
Ex: All students at York vs all the people in my family
-When populations are small (such as my family) you can study them in whole, without
leaving anyone out (the researcher can then feel confident about their findings, because they
have data from the entire population
-However, most times, samples must be used instead of populations because the population
of interest is much too large
- Samples make guesses about the wider population in which they are drawn
-Researchers can make conclusions about populations by studying samples
-2 Techniques of Sampling:
oProbability Sampling (with better external validity)
oNon-Probability Sampling
Probability Sampling: There is a known probability of each member from a population being
included in your sample (Ex: a box of black and white stones. All people in the class pick a stone,
and if you get a black stone, you will be included in the sample. If there are 3 black and 7 white,
everyone has a 30% chance of being included in the sample (students pick a stone and place it back
in the box after being picked))
-The sample is representative of the population (the sample looks like the population. Ex:
there are (roughly) 50% males and 50% females)
-The sample captures all aspects of the population
-How to get representative samples?
oPercentage of population (vs sample size): when researchers are interested in a
large population, they might end up with a large sample, but it is a very small
percentage of the entire population (it is the percentage that matters, not the size of
the actual sample)
oCompare demographics: the demographics of the sample should be representative
of the entire population, Ex: race, gender, socioeconomic status etc
oBeware of self-selection and bias: Bias makes the sample skewed (Ex: a survey is
conducted on an app that is only available on Apple iOS. Also, some people will
select themselves to participate, even though everyone has an equal change of
participating, some people will participate and some will not. Both self selection and
bias will skew data
- Most researchers do not use probability sampling
Non-Probability Sampling: When researchers don’t know the probability of population members
being included in the sample
-Samples are not randomly drawn
- Convenience Sampling: Researchers include people who are around to participate. They
take people who are conveniently available to be studied (Ex: URPP’s. Undergrads must do
the studies for marks, these people are available and are at the university, undergrads are
oPurposive Sampling: When people with a common characteristic are selected for
study (Ex: all people at York who are left handed)
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