Title: Introduction to Biostatistics (PUBHLTH 540) Hypothesis Testing
1Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing
- General Idea
- How unusual is the result?
- Test statistics
- Type I error (alpha level)
- p-value
- Type II error (beta level)
- Power1-beta
2Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
- Total cholesterol (mg/dl) is measured on a simple
random sample of 32 women over the age of 60. Is
there evidence that mean cholesterol is different
in women of this age group as compared with women
under age 50? - Estimate of TC (see ejs09b540p36.sas)
- Plot histogram of SRS of n32 from women lt50.
(see ejs09b540p37.sas)
Result is very unusual relative to what wed
expect from sampling. Conclude the mean is
differnet.
244
3Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
- Histogram of distribution of sample
means/standardized value- - need to know mean and variance of TC for women lt
50. - use Z if variance is known, t if variance is
estimated
244
4Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
- Plot Histogram of distribution of sample means
under Null H - or histogram of standardized values of the
difference of the sample mean from the mean TC
for women lt 50 - need to know mean and variance of TC for women lt
50.
- use Z if variance is known, t if variance is
estimated
244
5Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
244
6Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
z8.08
7Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
z8.3
z8.32
8Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
- Is the result unusual?
- Decide a level of unusualness
- usually set at values so that 5 of time, sample
mean would be further away (also called TYPE 1
Error) - If in either direction, then 2.5 on either side,
and test is called 2-sided - Called 2-sided test
- If unusual is important only in one direction
(drug lowers cholesterol), then put all 5 on one
side - Called 1-sided test
- Null hypothesis is usual or commonly accepted
position. - Alternative hypothesis is what you want to prove
9Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
Null Hypothesis
10Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
AlternativeHypothesis
11Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
Critical region
2-sided test
Unusual
Unusual
12Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
Critical region
1-sided test
Unusual
13Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
2-sided test
Unusual
Unusual
14Introduction to Biostatistics (PUBHLTH 540)
Hypothesis Testing-General Idea
1-sided test
Unusual
15Introduction to Biostatistics (PUBHLTH 540)
Power of a Test-General Idea
1-sided test
Unusual
16Introduction to Biostatistics (PUBHLTH 540)
Power of a Test-General Idea
1-sided test
Unusual
17Introduction to Biostatistics (PUBHLTH 540)
Power of a Test-General Idea
1-sided test
1-sided test
Unusual
Unusual
18Introduction to Biostatistics (PUBHLTH 540)
Power of a Test-General Idea
1-sided test
1-sided test
Unusual
Unusual
19Introduction to Biostatistics (PUBHLTH 540)
Power of a Test-General Idea
1-sided test
1-sided test
1-sided test
Unusual
Unusual
20Introduction to Biostatistics (PUBHLTH 540)
Power- example
- Assume in one population, we know TC for males is
normally distributed with mean 220, and variance
1524. Our interest is in mean TC for men in a
different population. We would like to know
whether TC is less in the other population (vs a
null hypothesis that it is equal to or greater
than 220). Consider a one sided test of the null
hypothesis. Suppose we select a sample of n25
subjects from the new population. Let us test
the null hypothesis that the mean is 220, versus
an alternative hypothesis that the mean is 205
based on a one sided test with n25. What is the
power of the test? - Figure out the rejection region under the null
hypothesis in terms of the distribution of sample
means. - Make a sketch indicating the critical region (on
the scale of TC). - Use the z-applet with an assumption that the
alternative hypothesis is true to figure the
power.
21Introduction to Biostatistics (PUBHLTH 540)
Power- example
- Figure out the rejection region under the null
hypothesis in terms of the distribution of sample
means.
22Introduction to Biostatistics (PUBHLTH 540)
Power- example
- Figure out the rejection region under the null
hypothesis in terms of the distribution of sample
means.
23Introduction to Biostatistics (PUBHLTH 540)
Power- example