# Course Identification

Introduction to statistics for life sciences
20243342

Keren Taub
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## Course Schedule and Location

2024
Second Semester
Sunday, 16:00 - 19:00, Weissman, Auditorium
07/04/2024
07/07/2024

## Field of Study, Course Type and Credit Points

Life Sciences: Lecture; 4.00 points
Life Sciences (Computational and Systems Biology Track): Lecture; Obligatory; Regular; 4.00 points
Life Sciences (ExCLS Track): Lecture; Obligatory; Regular; 4.00 points

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No

120

English

## Attendance and participation

Expected and Recommended

Numerical (out of 100)

20%
80%

Examination

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N/A
-
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-
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## Syllabus

This course will introduce students to basic and mid-level statistical methodology. The course will familiarize the students with basic statistical concepts
(median, mean, variance, etc.) and carry on to more complex statistical tools such as distributions, hypothesis testing, and more. The bulk of the course is

intended for covering the most popular statistical tests in use: t-tests, chi-square, ANOVA, regressions, and more. We will discuss both parametric and non-
parametric statistical tests. The principal aim of the course is to instill the students with a basic understanding of statistical thought, so they can apply

statistical reasoning in new and unfamiliar areas of research.
Topics to be discussed (not necessarily in the below mentioned order):
1. Basic concepts: Measurement scales; Variables; Transformations; Data plotting
2. Central tendencies; Measures of variability
3. The Normal distribution; Sampling distributions
4. Hypothesis Testing; Type I and type II errors
5. One-sample t-test: Power; Confidence Interval
6. Two-sample t-tests (matched and independent samples)
7. Probability, Combinatorics, Bayes' rule
8. The binomial distribution; chi-square test
9. Correlation & Regression
10. Multiple Regression
11. ANOVA
12. [Post-hoc comparisons
13. Repeated measures designs
14. Nonparametric tests

## Learning Outcomes

Upon successful completion of this course students should be be able to:
1. Execute different basic and medium level prominent statistical tests.
2. Differentiate between statistical needs and their applicable tests.
3. Apply the knowledge gained in this course in new and unfamiliar areas of research.