Be sure to
print out handouts for:
I. Introduction
A.
Conceptual perspective
 what are doing when we analyze quantitative data?
1. Computing
statistic that represents the data (e.g., mean differences)
2.
Results (e.g., mean differences) can be due to IV, confound, or error
3. Comparing the results (e.g., mean
differences) we obtain with what we might expect by
chance.
4. If
determined unlikely to have occurred by chance, then infer results
(e.g., mean
differences)
are "real",
that they are "statistically significant"
B. The role of probability,
chance and error
1. Use principles of
probability
(likelihood) to make decisions about data
2. Could these results have occurred by chance?
e.g.,
consider the mean scores of two groups 12.0 and 13.0. Are they
really different? Or did they different simply by chance?
All
things being equal, we are more convinced when we see larger differences
between means. Why?
All things
being equal, we are more convinced when standard deviations are low.
Why?
All things
being equal, we are more convinced when numbers are participants are
high. Why?
II.
Hypothesis testing
A.
Null hypothesis/Experimental hypothesis
B.
Decision:
Fail to reject vs. reject

reject null = statistical significance
C.
Making decisions and making mistakes
Possible
outcomes:


Decision



Reject Null

Fail to reject Null

What is true in
the population?

Null is false

CORRECT
(Power)

Type II error
(β)

Null is true

Type I error
(α)

CORRECT

1.
Type I error
2.
Type II error
Which error is worse?
3.
Power
Power
is increased by:
III.
Inferential Statistics
A. What is
meant by
inference?
B.
ttest
t
= association/lack of association
1.
calculate means
for each group
2.
calculate variance
for each group; calculate pooled variance
3.
compute t
4.
find critical t, given specified alpha
and
degrees
of freedom
5.
compare obtained t with critical t; make decision
C.
Chisquare (handout)

Calculate marginal frequencies

Calculate expected values for each cell

Calculate chisquare

Find
critical chisquare, given alpha and
degrees
of freedom

Compare
chisquare with critical chisquare; make decision
D. Pearson r (handout)
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