Class Notes (1,100,000)
CA (620,000)
U of A (10,000)
PSYCO (1,000)
PSYCO104 (400)
Lecture 14

PSYCO104 Lecture Notes - Lecture 14: Stratified Sampling, Soundness, Internal Validity

Course Code
Geoff Hollis

This preview shows half of the first page. to view the full 2 pages of the document.
October 8 2014
Random vs Stratified Sampling
Stratified Sampling is sometimes used in place of random sampling when there
are low-probability subgroups you are interested in explicitly representing.
I.e. Sampling age groups -- if there are 30% young adult Canadians,
systematically ensure that your data set includes 30% young adult Canadians.
Within the subgroup, return again to random sampling.
Making Claims
Correlation tests are used to detect whether two types of measures are
to each other.
When a change in one variable is accompanied by a proportional change
another variable, we say they are correlated.
E.g. Does aggression increase with frequency of video game
Correlations can be visualized with scatterplots.
Statistical tools exist to determine strength of correlation. "The
coefficient" referred to as 'r' gives an estimate of strength.
0 means no correlation. Range of 1 to -1.
Causation - Observing correlations is not sufficient to establish cause and
effect. For instance, observing a correlation between spanking and adult
deliquency is not enough to establish that spanking your child causes them to
be maladapted.
There can be four types of reasons why you might observe a correlation.
X causes Y
Y causes X
X and Y are unrelated, but both depend on some third variable.
Or just random happenchance.
Set up two identical situations, with only one change. If
differences are
observed, it must have been caused by the change which was
In practice, it is difficult to only change one thing.
Random Assignment
You're Reading a Preview

Unlock to view full version