Transcript Course Overview

3/29/2016
Statistics for Molecular Biology and Bioinformatics
Instructor: Ron S. Kenett
Email: [email protected]
Course Website: www.kpa.co.il/biostat
Course textbook: MODERN INDUSTRIAL STATISTICS,
Kenett and Zacks, Duxbury Press, 1998
(c) 2000, Ron S. Kenett, Ph.D.
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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
(c) 2000, Ron S. Kenett, Ph.D.
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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
Mini Project Description
Date of Review:
Student Name:
Student Name:
Student Name:
3/29/2016
Student ID:
Student ID:
Student ID:
Research sponsor:
email:
room/building:
phone:
Project Name:
Problem Background:
Data Characteristics:
Assumptions:
Questions to investigate:
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Simple regression
Multiple regression
Design of Experiments
ANOVA
Student ID:
Student ID:
Student ID:
Hypothesis testing
Confidence intervals
Point estimation
Bootstrapping
Probability distributions
Random variables
Student Name:
Student Name:
Student Name:
Neasures of association
Measures of dispertion
Measures of location
Descriptive Statistics
/Demonstration of
Level of Understanding
Statistical Tools in mini project
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Project Name:
Exam grade:
Exam grade:
Exam grade:
Sub-Totals:
.
Statitical Tools
Total:
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The mini-project - 3
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Date of Review:
Student Name:
Student Name:
Student Name:
Project Name:
Scientific Evaluation
Achieved
Meaningfull Results
Applied Statitical
Tools
/Demonstration of
Level of Achievement
mini project results
Research sponsor:
Mini project results
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The mini-project - 4
The Process of Solving Problems with Statistics
INPUT
PLAN
• Obje ctive s
• Que s tions
• As s umptions
• S cope s
• Approa ches
• S tra te gy
COLLECT
• Obs e rve
• Ga ther
• Code
• E dit
• Trans form
PRESENT
ANALYZE
• Plot
• Look
• Es tima te
• Dia gnos e
• Conclude
OUTPUT
• Interpre t
• De s cribe
• Ans we r
• Re comme nd
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Basic concepts and notation
Population


N
Sample
X
(c) 2000, Ron S. Kenett, Ph.D.
n
S
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Statistical Inference
Population


Descriptive
Statistics
N
Probability
Sample
X
n
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Statistical Issues in Life Sciences
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