This syllabus assumes a 15-week semester, meeting once or twice a week for a standard laboratory period (e.g., 2-3 hours). Adjustments may be needed based on the specific needs of your institution, class, and available resources.

Course Title: Statistical Biology Laboratory

Instructor:

Course Description:
This laboratory course is designed to complement the concepts covered in the Statistical Biology lecture course. Students will gain hands-on experience with statistical methods and tools commonly used in biological research. Practical skills will be developed through data analysis, interpretation, and presentation.

Week 1-2: Introduction to R Programming and Data Handling

Overview of R programming language
Basics of data types, data structures, and functions
Importing and manipulating biological data in R
Exploratory data analysis (EDA) techniques
Week 3-4: Descriptive Statistics in Biology

Mean, median, and mode calculations
Variability and standard deviation
Box plots and histograms for biological datasets
Interpretation of summary statistics
Week 5-6: Probability and Distributions in Biology

Probability distributions in biology (normal, binomial, Poisson)
Sampling distributions and the Central Limit Theorem
Confidence intervals and hypothesis testing
Week 7-8: Statistical Inference in Genetics

Hardy-Weinberg equilibrium testing
Chi-square tests for genetic data
Introduction to genetic linkage analysis
Week 9-10: Regression Analysis in Ecology

Simple linear regression
Multiple linear regression
Interpretation of regression models in ecological studies
Practical applications in ecology
Week 11-12: Bioinformatics and Computational Biology

Introduction to bioinformatics tools and databases
Sequence alignment and analysis
Genome-wide association studies (GWAS)
Week 13-14: Population Dynamics and Epidemiology

Modeling population growth and dynamics
Analysis of epidemiological data
Spatial analysis in disease ecology
Week 15: Final Project and Presentation

Students work on a final project applying statistical methods to a biological dataset of their choice
Prepare a written report and give a short presentation to the class
Assessment:

Weekly Lab Reports: 30%
Midterm Exam: 20%
Final Project and Presentation: 30%
Participation and Attendance: 20%
Textbook:
"Statistical Methods in Biology" by Ronald A. Fisher and John H. McDonald

Software:
R Statistical Software, Bioconductor, and relevant bioinformatics tools.