1 / 12

Statistics for Molecular Biology and Bioinformatics

Statistics for Molecular Biology and Bioinformatics. Instructor: Ron S. Kenett Email: ron@kpa.co.il Course Website: www.kpa.co.il/biostat Course textbook: MODERN INDUSTRIAL STATISTICS, Kenett and Zacks, Duxbury Press, 1998. Course Syllabus. Understanding Variability

jberner
Download Presentation

Statistics for Molecular Biology and Bioinformatics

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. Statistics for Molecular Biology and Bioinformatics Instructor: Ron S. Kenett Email: ron@kpa.co.il 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.

  2. 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.

  3. 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 (c) 2000, Ron S. Kenett, Ph.D.

  4. 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 (c) 2000, Ron S. Kenett, Ph.D.

  5. 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 (c) 2000, Ron S. Kenett, Ph.D.

  6. The mini-project - 1 (c) 2000, Ron S. Kenett, Ph.D.

  7. The mini-project - 2 (c) 2000, Ron S. Kenett, Ph.D.

  8. The mini-project - 3 (c) 2000, Ron S. Kenett, Ph.D.

  9. The mini-project - 4 The Process of Solving Problems with Statistics (c) 2000, Ron S. Kenett, Ph.D.

  10. Basic concepts and notation Population N Sample n (c) 2000, Ron S. Kenett, Ph.D.

  11. Descriptive Statistics Probability Statistical Inference Population N Sample n (c) 2000, Ron S. Kenett, Ph.D.

  12. Statistical Issues in Life Sciences Design Experiments Synthesize Compare Summarize Track changes Assess Similarities Analyze (c) 2000, Ron S. Kenett, Ph.D.

More Related