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 Statistics for Laboratory Scientists I  posted by  member7_php   on 3/9/2009 Add To Favorites
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Abstract/Syllabus:

## Statistics for Laboratory Scientists I

### Spring 2006 Course

Karl Broman

Biostatistics

#### Description

This course introduces the basic concepts and methods of statistics with applications in the experimental biological sciences. Demonstrates methods of exploring, organizing, and presenting data, and introduces the fundamentals of probability. Presents the foundations of statistical inference, including the concepts of parameters and estimates and the use of the likelihood function, confidence intervals, and hypothesis tests. Topics include experimental design, linear regression, the analysis of two-way tables, sample size and power calculations, and a selection of the following: permutation tests, the bootstrap, survival analysis, longitudinal data analysis, nonlinear regression, and logistic regression. Introduces and employs the freely-available statistical software, R, to explore and analyze data.

# Syllabus

#### Course Description

Introduces the basic concepts and methods of statistics with applications in the experimental biological sciences. Demonstrates methods of exploring, organizing, and presenting data, and introduces the fundamentals of probability. Presents the foundations of statistical inference, including the concepts of parameters and estimates and the use of the likelihood function, confidence intervals, and hypothesis tests. Topics include experimental design, linear regression, the analysis of two-way tables, sample size and power calculations, and a selection of the following: permutation tests, the bootstrap, survival analysis, longitudinal data analysis, nonlinear regression, and logistic regression. Introduces and employs the freely-available statistical software, R, to explore and analyze data.

#### Course Objectives

• Graphical displays of data
• Basic experimental design
• Basic probability
• Confidence intervals and tests of hypotheses

Required:
ML Samuels, JA Witmer (2002) Statistics for the life sciences, 3rd ed, Prentice Hall.

Recommended:
L Gonick, W Smith (1994) Cartoon guide to statistics. HarperCollins.
P Dalgaard (2002) Introductory statistics with R, Springer-Verlag.

## Schedule

SESSION # TOPIC ACTIVITIES

1 Overview; What Is Statistics?
2 Displaying Data Badly; Data Summaries
3 Experimental Design
4 Observational Studies
5 Probability, Conditional Probability
6 Examples, Bayes's Theorem
7 More Examples
8 Random Variables, Distributions, Binomial, Poisson
9 Normal Distribution, Multiple Random Variables
10 Sampling Distributions; Central Limit Theorem
11 More of the Same
12 Maximum Likelihood Estimation
13 Confidence Interval (CI) for the Mean
14 CIs for Differences Between Means, CI for Population SD

15 Tests of Hypotheses
16 Tests for Differences Between Means
17 Calculation of Sample Size and Power
18 Permutation Tests and Other Non-Parametric Tests
19 Confidence Interval for a Proportion
20 Uses and Abuses of Tests

21 Transformations and Outliers
22 Analysis of Gene Expression Microarrays
23 Identifying Essential Genes in M tuberculosis
24 Exam

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