Todays Schedule
Notation
Summary Statistics for Quantitative Data
location
spread
17 April 2003
Biostatistics 6650-L2
1
Notation
Assume we have a random sample of observed data
values:
x1 , x2 ,., xn
Total sample size: n
Summation symbol is
n
x
i
Todays Schedule
Frequency Distributions
Graphical Summaries
Data Quality Control
18 April 2003
Biostatistics 6650-L3
1
Frequency Distributions
Provides a very useful tabular summary of
any type of data
ordered display of all n sample data values and
Todays Schedule
Probability
notation
laws
example
Screening test measures
sensitivity/specificity
positive(negative) predictive value
ROC curves
24 April 2003
Biostatistics 6650-L4
1
Probability
Nothing is impossible. Some things are
just less li
Todays Schedule
Discrete random variables
Definition/examples
Probability distribution function
Cumulative distribution function
Population mean/variance
Permutations/Combinations
Binomial distribution
Poisson distribution
Handout Binomial/Poisson Tab
Todays Schedule
Continuous random variables
Probability density function
Cumulative distribution function
Normal Distribution
Standard Normal Distribution
Calculating probabilities
Conversion
Normal approximation to Binomial/Poisson
Handout Normal
Todays Schedule
Estimation of the population mean
Central limit theorem
Interval estimation
Mean of continuous data
known
unknown(
2 May 2003
t-distn)
Binomial Proportion
Poisson
Sample size for CIs
Variance( chi-square distn)
Biostatistics 6650-L7
HO
22 May 2003
Biostatistics 6650-L8
1
Todays Schedule
Hypothesis Testing: one sample
general approach/procedure
example: one sample normal, known
P-values
Relationship between hypothesis testing and
confidence intervals
22 May 2003
Biostatistics 6650-L
23 May 2003
Biostatistics 6650-L9
1
Todays Schedule
Hypothesis Testing: one sample
Normal test
review 3 known(one sample z-test)
3 unknown (one sample t-test)
Paired t-test
Binomial proportions
Making inferences from hypothesis tests
23 May 2003
Bi
30 May 2003
Biostatistics 6650-L10
1
Todays Schedule
Hypothesis Testing: Two Sample Tests
General approach
Two-sample t-test
Large sample Binomial
30 May 2003
Biostatistics 6650-L10
2
General Approach
Comparing Two Populations
Two scenarios:
Depend
30 May 2003
Biostatistics 6650-L11A
1
Todays Schedule
ANOVA
general/assumptions
example
30 May 2003
Biostatistics 6650-L11A
2
ANOVA: general
What if we want to compare means for more than
2 groups?
Could use multiple 2-sample t-tests
5 groups.5C2 or
05 June 2003
Biostatistics 6650-L11B
1
Todays Schedule
ANOVA
example
contrasts in means
Multiple Comparison Procedures
05 June 2003
general issue
solutions
example
controversy
Biostatistics 6650-L11B
2
ANOVA: testing for normality
Shapiro-Wilk W test
6 June 2003
Biostatistics 6650-L12
1
Todays Schedule
Contingency tables
2x2 tables
RxC tables
1-way tables(Goodness of fit)
McNemars test for paired(correlated) proportions
6 June 2003
Biostatistics 6650-L12
2
2x2 Tables
Recall the test for comparing tw
19 June 2003
Biostatistics 6650-L13
1
Todays Schedule
Non-parametric Statistics(9.1-9.4)
Introduction
Sign test
Signed Rank test
Rank Sum test
Kruskal-Wallis test(12.7)
Summary
19 June 2003
Biostatistics 6650-L13
2
Introduction
Parametric methods
Metho
Todays Schedule
Sample size and power for hypothesis
testing
Power, general
1-sample tests
Power
Sample size
2-sample tests
Power
Sample size
References/Software
Examples using Beyer and Cochran SS tables (handout) .
20 June 2003
Biostatistics 6
26 June 2003
Biostatistics 6650-L15
1
Todays Schedule
Association of continuous X with continuous Y
brief introduction
Scatter plots
Correlation
Pearson/Spearman
Regression
simple linear regression
least squares
Wrap-up
26 June 2003
Biostatistics