עקרונות סטטיסטיים בניסויים (0400.6000)

 
שם הקורס באנגלית: Statistics
 
מרצה הקורס: ד"ר לוי סיגל
 
ימים ושעות הקורס

ימים ושעות הקורס

סוג: שיעור

מספר קורס

סמסטר

יום

משעה

עד שעה

בניין

חדר

0400.6000.01

ב

ד

11:00

14:00

שרמן

002

 

 

סוג: תרגיל

 

מספר קורס

סמסטר

יום

משעה

עד שעה

בניין

חדר

שם המתרגל

0400.6000.02

ב

ה

08:00

10:00

בריטניה

005

גב' גפטר לי

 
סילבוס:
Aims
 
This course is designed to give Masters and PhD students in Biology basic tools and understanding in Statistical Theory, its applications, and computational technics. This course does not require any prior knowledge in Statistics, however requires basic computer skills.
 
Specific Learning Outcomes:
By the end of this course, students will:
• Acquire basic knowledge in Statistical Theory; Probability Theory; Sampling Theory; Estimation Theory & Statistical Decision-Making; Regression Analysis.
• Acquire sufficient CADA (Computer Aided Data Analysis) skills for conducting independent Graduate-level research in Biology.
 
FORMAT AND PROCEDURES
• Lectures cover both theory and some applications.
• Recitation classes are designed to give students further problem-solving techniques and training in CADA.
• Direct all requests regarding administrative issues to the TA via e-mail. Course lecturer is to be informed of such requests by the TA only.
 
COURSE REQUIREMENTS
Class attendance and participation policy
• Lectures and recitation classes are not mandatory, however attendance is recommended.
• Please use discretion when deciding not to attend lectures or recitation classes. Course instructors are not obligated to assist students in bridging knowledge gaps due to low attendance rates.
 
Assignments
Ten (10) written assignments will be given throughout the semester. Each complete assignment grants 1 point to the final grade, up to a total of 10 points.
 
 
Course readings
All reading materials are non-mandatory and non-binding. The exam only covers materials taught by Dr. Levy!
 
Suggested readings:
• Watt, T. A., McCleery, R. H., & Hart, T. (2007). Introduction to statistics for biology. CRC Press.
• Quinn, G. P., & Keough, M. J. (2002). Experimental design and data analysis for biologists. Cambridge University Press.
• Van Emden, H. (2012). Statistics for terrified biologists. John Wiley & Sons.
 
Suggested practice materials:
Stephens, L. J. (1997). Schaum's Outline of Beginning Statistics.
***For further elaborations on suggested reading and practice materials please refer to the tentative course schedule.***
 
 
Grading procedures
• In accordance with the hereinabove assignments clause- the final course grade will be composed of 90% final exam, 10% assignment submission.
• Exams are not graded on a curve.
 
 
ACADEMIC INTEGRITY
• Each student in this course is expected to abide by the Tel-Aviv University Code of Academic Integrity.
• Any work submitted by a student in this course for academic credit will be the student's own work.
• Students are encouraged to study together and to discuss information and concepts covered in lecture and the sections with other students. Students can give "consulting" help to or receive "consulting" help from such students. However, this permissible cooperation should never involve one student having possession of a copy of all or part of work done by someone else- student, tutor, or otherwise.
• Should copying occur, both the student who copied work from another student and the student who gave material to be copied will both automatically receive no credit for the assignment. Penalty for violation of the plagiarism-ban can also be extended to include failure of the course and disciplinary actions.
 
TENTATIVE COURSE SCHEDULE
 
Weeks 1-2
• Review on Descriptive Statistics: Measures of central tendency; Measures of dispersion; Graphs and charts; Linear Transformation; Common distribution shapes.
Suggested reading:
Further Practice: SCHAUM: Chapters 1-3, pp. 1-62.
 
 
Weeks 3-5
• Basic Probability Theory; Bayesian Probability Theory; Random variables (i.e., RV); Mean and variance of RVs.
• The Normal distribution.
• Central Limit Theorem.
Suggested reading:
Further Practice: SCHAUM: Chapter 4, pp. 63-88.
SCHAUM: Chapter 5, pp. 89-112. Note: All but Binomial Distribution are
non-mandatory course-materials.
SCHAUM: Chapter 6, pp. 115-139.
 
 
Weeks 6-7
• Statistical Estimation Theory: Sampling; Parameters vs. test statistics;
• Tests of hypotheses and significance of mean estimations in sampling populations with known variance.
• Type I and Type II errors, Power
Suggested reading:
Further Practice: SCHAUM: Chapter 7, pp. 140-165.
SCHAUM: Chapter 9, pp. 185-210.
 
 
Week 8
• Tests of hypotheses and significance of mean estimations in sampling populations with unknown variance: T-tests for single and paired samples.
Suggested reading:
Further Practice: SCHAUM: Chapter 10, pp. 211-248.
SCHAUM: Chapter 14, pp. 334-358.
 
 
Weeks 9-10
• Tests of hypotheses and significance on independent samples: T-tests.
• One-way ANOVA: Between and Within Samples variance; Explained and unexplained variation; ??2 measure of effect size. F test. Post Hoc tests.
• Two-way ANOVA: Interaction between factors; Suggested reading:
Further Practice: SCHAUM: Chapter 12, pp. 272-308.
 
 
Weeks 11-12
• Correlation and measures of association: Pearson’s ??2 Test; Cramer’s ??.
• Linear regression: application of ANOVA in regression analysis.
Suggested reading:
Further Practice: SCHAUM: Chapter 11, pp. 249-271.
SCHAUM: Chapter 13, pp. 309-333.
 
 
 
 
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