Transcript Lesson #34 Review and Summary Important Topics

Lesson #34
Review and
Summary
Important Topics
p, etc.
- Descriptive statistics  X, S, ˆ
- Basic probability, independence
- Sensitivity and specificity
- Relative risk, odds ratio
- Binomial distribution
- Normal distribution, standardizing
- Reading tables (Z, t, F, c2)
- Inference (C.I. and hypothesis testing)
- one mean
(one-sample t-test)
- two paired means
(paired t-test)
- two ind. mean
(pooled t-test)
- several means
(ANOVA)
- one proportion
(Z-test for one proportion)
- two proportions
(Z-test for two proportions)
- cat. var. association
(contingency table)
- num. var. association (correlation/regression)
A colleague had data on body
fat for runners and swimmers,
and performed a pooled t-test
to compare the two types of
athletes. I made similar
measurements for runners and
swimmers, but I also included
volleyball players. Now that I
have three groups, how do I go
about testing for a difference?
Our team has developed a new
medical technique that we think
will lead to better survival rates
than a standard technique. We
have two groups of patients; one
group which received the standard
technique, and another which
received our new technique. How
can we obtain statistical evidence
that our technique is better?
We have collected
data on 20 women who
are taking a certain
drug, and want to see
if the average age of
menopause of such
women is greater than
55 years old. How
does one make such
a statement?
At work, we wanted to look at
the effectiveness of a clean-up
effort at a nearby lake. A
pollution index was measured
at a number of sites around the
lake before the clean-up effort,
and again six months after.
The data was analyzed using
an ANOVA, where the two
time periods were the two
treatments. Is this OK, or
is there a better method?
I work as a volunteer for
the Red Cross, and one of my
supervisors wants me to look
for a relationship between
blood type and whether or
not the person has ever
donated blood. I have a
random sample of 150 people
that I took from a large
university class, where I
asked people these two
questions. What kind of
analysis should I use?
A physician in my office
wishes to quantify the
relationship between the
amount of moderate to
strenuous exercise and
systolic blood pressure.
The exercise variable is
converted to METS, which
is a quantitative variable. I
have suggested she use a
correlational analysis. Do
you have any further
suggestions?
I recently saw a study
which said that 30% of
teenagers in a rural area
eat a nutritious diet. I
expect that this
percentage is even lower
in the urban area where I
live. How can I go about
finding out if this is true?
I have asked a bunch of
teenagers at a local school
about their diet.
My wife works for the
Department of Mental Health.
She says they want to see if
there is a difference in the
average levels of a certain
blood chemical between people
with depression and those not
suffering from depression.
How does one go about
performing such an analysis?