39.39 66.67 39.39
N = 30 87.88 48.48 54.55
Mean = 65.02 72.73 81.82 45.45
SD = 15.14 75.76 63.64 45.45
30.3 57.58 78.79
66.67 60.61 69.7
15.14 75.76 66.67 72.73
60.61 93.94 75.76
30 75.76 84.85 69.7
66.67 63.64 60.61
Standard error = 2.76 N = 30
Mean = 65.02
SD = 15.14 Selection of research participants
The selection of research participants
- Who do we measure?
- Populations and samples
- Sampling techniques - How can we ever know that a sample actually reflects the entire population?
• Normally distributed means of sample mean
• Standard error
Who do we measure?
- Empirical research in psychology involves testing individuals.
• Who do we measure?
• How many participants should we test?
- Definition: The set of individuals of interest to a researcher.Aset of entities concerning
which statistical inferences are to be drawn
- Can be:
• The students registered in PSYC 2001 D (Fall 2011) at Carleton University
Easy to get reasonable assumption. If class average is 70%, on the day of the test
we knew 70% of the material on average.
• Ottawa Senators’Fans
Would have to be specific as “people registered in the fan club”
If you see every senator fan across the world, harder to qualify
• Citizens of Canada
Census every 4 years. Even then there is always change. Can’t sample quickly
- For multiple reasons, it is not typically possible to test entire populations. Instead,
samples are obtained.
- Sample: Asubset of a given population. The set of individuals of interest to a researcher.
Aset of entities concerning which statistical inferences are to be drawn. - Sampling: The variety of ways of selecting individuals to participate in a research study.
How can we ever know that a sample actually reflects the entire population?
- One spoonful of soup can accurately represent the taste of the whole pot so long as
everything is well-stirred.
- Sample representativeness: The extent to which the characteristics of a sample reflect
those of the population.
Sample characteristics = Population characteristics
Sample characteristics ≠ Population characteristics
Dewey defeats Truman!
- Unrepresentative sample (telephone users) led to an overestimation of the Republican
- Truman shows the newspaper that say that Dewey defeated Truman, but Truman was the
one who won
- Biased because mostly people in higher class were the ones who answered the phone
polls, and the poorer people did not because they did not have phones
- Probability sampling: The population is known and each individual has a specifiable
probability of being selected.
- Random:Asampling process that ensures that each individual in the population has an
equal chance of being selected.
• Choosing people without any bias (Ex: all names in a hat, stir, and pick out names)
• Trying to set it up so there is no bias
- Other probability sampling methods include:
• Proportionate random
• Stratified random • Cluster
Populations and sample me