STAT 210
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Course Number |
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STAT 210 |
Name |
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Probability Theory |
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| 2) |
Credits |
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3 |
Contact Hours |
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39 Hrs Lecture |
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| 3) |
Course Coordinator’s Name |
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Dr. Hamid H. Ahmed |
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| 4) |
Text Book |
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A First Course in Probability Sheldon Ross , 8th Edition (2010)
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| 5) |
Other References |
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Fundamentals of Applied Probability and Random Processes, 2nd Edition Oliver C. Ibe University of Massachusetts, Lowe LL, Massachusetts ( 2005)
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| 6) |
Specific Course Information |
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a. |
Synopsis |
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This course aims to introduce students to the concepts of the theory of probability and how it is used in decision-making with the study of random variables and probability distributions and their characteristics.
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b. |
Prerequisites |
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STAT 110-General Statistics
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c. |
Type of Course |
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Core |
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| 7) |
Course Learning Outcomes (CLO) |
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Students will be able to:
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Knowing about the basics probability laws and rules. |
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Use these laws and rules to solve various examples. |
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Understanding the main probability concepts.. |
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Familiarize student with proper logical thinking and winning skills necessary to resolve issues related to the probability. |
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| 8) |
Course Topics and Their Duration |
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Number
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Description
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Duration in weeks
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1
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Combinatorial Analysis (Counting rules, Permutations, Combinations, Binomial Theorem). Basic Probability concepts
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2
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2
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Conditional probability, Total Probability and Bayes theorem and Tree Diagram. Independence events- Applications of Permutations and combinations in Probability.
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1
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3
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Random variable, cumulative distribution function,. Discrete random variable, probability mass function, and CDF of a discrete random variable, Continuous random variable, probability density function, CDF,
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2
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Midterm Exam 1
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4
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Expectation, variance for discrete and continuous random variable. Moments about zero and moments about mean. Moment generating function for discrete and continuous random variable.
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5
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Discrete probability distributions : Bernoulli dist’n (p.d.f, CDF, mean, variance, m.g.f, mean and variance from m.g.f) o
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6
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Binomial dist’n (p.d.f, CDF, mean, variance, m.g.f, mean and variance from m.g.f) o Poisson dist’n (p.d.f, CDF, mean, variance, m.g.f, mean and variance from m.g.f)
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2
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Midterm Exam 2
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7
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Geometric dist’n (p.d.f, CDF, mean, variance, m.g.f, mean and variance from m.g.f). o Hyper geometric dist’n (p.d.f, CDF, mean, variance, m.g.f, mean and variance from m.g.f)
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1
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8
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Uniform dist’n (p.d.f, CDF, mean, variance, m.g.f, mean and variance from m.g.f) o Exponential dist’n (p.d.f, CDF, mean, variance, m.g.f, mean and variance from m.g.f)
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2
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9
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Normal distribution (mean, variance, m.g.f) Standard normal variable. Application of standard normal variable,
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1
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10
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Techniques of simulation
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1
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Final Exam
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Class Schedule |
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Meet 60 minutes three times/week
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| 10) |
Assessment Tools and Marks Distribution |
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Assessment Type
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Percentage of Mark
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Homework and Quizzes
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10 %
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Midterm Exam 1
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25 %
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Midterm Exam 2
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25 %
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Final Exam
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40 %
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Total
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100 %
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Last Update
2/18/2017 8:38:28 PM
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