Statistics for Molecular Biology and Bioinformatics

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Statistics for Molecular Biology and
Bioinformatics
Instructor Ron S. Kenett Email
ron_at_kpa.co.il Course Website www.kpa.co.il/biosta
t Course textbook MODERN INDUSTRIAL
STATISTICS, Kenett and Zacks, Duxbury Press, 1998
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Course Syllabus

• Understanding Variability
• Variability in Several Dimensions
• Basic Models of Probability
• Sampling for Estimation of Population Quantities
• Parametric Statistical Inference
• Computer Intensive Techniques - Bootstrapping
• Multivariate Analysis - Multiple Linear
  Regression
• Sequential Methods - Statistical Process Control
• Design of Experiments

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Course Emphasis

• Interpretation of Statistical tools and methods
• Reliance on Statistical software (MINITAB)
• Learning by doing
• Interactive classroom environment
• Responsibility for the course is shared by
• The instructor
• The students
• The researchers behind the mini-projects

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Grading Policy

• A mini-project 2-3 students per project
• An exam at the end of the course
• Final grade split 50-50
• Difficulty level of final exam will depend on
• level of efforts put into project

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The mini-project

• Defined in collaboration with a researcher
• Has to be completed at the end of the semester
• Has to be interesting/useful
• Should provide opportunity to apply one (or more)
• Statistical tool taught in the course

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The mini-project - 1
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The mini-project - 2
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The mini-project - 3
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The mini-project - 4
The Process of Solving Problems with Statistics
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Basic concepts and notation
Population
N
Sample

n
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Statistical Inference
Population
N
Sample

n
12
Statistical Issues in Life Sciences
Design Experiments
Synthesize
Compare
Summarize
Track changes
Assess Similarities
Analyze