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Abstract/Syllabus:

Statistics for Laboratory Scientists I

Spring 2006

Graphic presentation of treatment and control group response data

Course

Instructor

Karl Broman

Offered By

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

Readings

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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