Course ID: | STAT 3120. 3 hours. |
Course Title: | Introduction to Probability for Life Sciences |
Course Description: | An understanding of probability and uncertainty in real-world
situations. Case studies of the role of uncertainty in the
life sciences. Analyzing chance phenomena to identify the
underlying probabilistic principles and translating them into
probability distributions or simulations. Introduction to
random variables, expected values, and variance in applied
settings to understand decision making in the face of
variability. Introduction to common discrete and continuous
random variables and their applications to the life sciences.
Extensive use of computer simulations to aid in conceptual
understanding. |
Oasis Title: | Intro to Prob for Life Science |
Prerequisite: | MATH 2250 or MATH 2250E or MATH 2300H or MATH 2400 or MATH 2400H |
Semester Course Offered: | Offered spring semester every year. |
Grading System: | A-F (Traditional) |
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Course Objectives: | This course is intended for students in the life sciences who
require an understanding of probability and its applications.
Upon completion of the course, students will be able to:
- Understand the importance of randomness in biological
processes and in interpretation of scientific results.
- Analyze random phenomena and identify the underlying
principles determining them.
- Identify when common probability distributions fit random
phenomena.
- Construct and run computer simulations to model simple
random phenomena.
- Apply probabilistic concepts to solving problems in health
sciences and biology.
- Use statistical software to calculate probabilities from
named discrete and continuous probability distributions.
- Interpret the expected value of a random variable and a
linear function of a random variable.
- Interpret the variance and standard deviation of a random
variable and a linear function of a random variable.
- Understand joint and conditional probability of multiple
random variables.
- Understand Bayes theorem with applications to health
sciences and biology. |
Topical Outline: | This course will cover case studies of randomness in biology;
identifying principles underlying random processes;
translating these principles into simple simulations; recognizing
when those rules imply common probability distributions;
properties of common distributions, including binomial, Poisson,
normal, and gamma distributions; expectation, variance, and
other properties of random variables; joint and conditional
probability; simulations involving multiple random variables. |
Honor Code Reference: | Student taking this class will be expected to follow and adhere
to UGA's Honor Code which can be found at
https://ovpi.uga.edu/academic-honesty/academic-honesty-policy. |