Ivo Dinov
UCLA Statistics, Neurology, LONI
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Statistics 13, (1)
Fall 2006
Introduction to Statistical Methods
for the Life and Health Sciences

 Final Review
1. Introduction. Statistics and the Life Sciences. Variation, Uncertainty and Chance.

2. Description of Populations and Samples. Introduction. Frequency Distributions: Techniques for Data. Frequency Distributions: Shapes and Examples. Descriptive Statistics: Measures of Center. Boxplots. Measures of Dispersion. Samples and Populations: Statistical Inference.

3. Random Sampling, Probability, and the Binomial Distribution. Probability and the Life Sciences. Random Sampling. Introduction to Probability. Probability Trees. Probability Rules (Optional). Density Curves. Random Variables. The Binomial Distribution. Fitting a Binomial Distribution to Data (Optional).

4. The Normal Distribution. The Normal Curves. Areas Under a Normal Curve. Assessing Normality.

5. Sampling Distributions. Basic Ideas. Dichotomous Observations. Quantitative Observations. Illustration of the Central Limit Theorem. The Normal Approximation to the Binomial Distribution

6. Confidence Intervals. Statistical Estimation. Standard Error of the Mean. Confidence Interval. Planning a Study to Estimate. Conditions for Validity of Estimation Methods. Confidence Interval for a Population Proportion.
7. Comparison of Two Independent Samples. Standard Error of (y1 - y2). Confidence Interval. Hypothesis Testing: The T-test. Further Discussion of the t-test. One-Tailed Tests. More on Interpretation of Statistical Significance. Student's T: Conditions and Summary. More on Principles of Testing Hypotheses. The Wilcoxon-Mann-Whitney Test.

8. Comparison of Paired Samples. The Paired-Sample T-Test and Confidence Interval. The Paired Design. The Sign Test. The Wilcoxon Signed-Rank Test. Further Considerations in Paired Experiments.
10. Analysis of Categorical Data. Inference for Proportions: The Chi-Squared Goodness-of-Fit Test. The Chi-Squared Test for a 2 X 2 Contingency Table. Independence and Association in a 2 X 2 Contingency Table.
11. Comparing the Means of Many Independent Samples. The Basic Analysis of Variance. The Analysis of Variance Model.
12. Linear Regression and Correlation. The Fitted Regression Line. Parametric Interpretation of Regression: The Linear Model. Statistical Inference Concerning b1. The Correlation Coefficient. Guidelines for Interpreting Regression and Correlation.

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