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Cyprus International University
TR

INTRODUCTION TO PROBABILITY AND STATISTICS

Course
MAT205 - INTRODUCTION TO PROBABILITY AND STATISTICS
Department
Institute of Graduate Studies and Research
Course Type
Scientific Preparation
Status
Required
Language
English
Credit
0
ECTS
0
T+P+L
0 + 0 + 0
Course Coordinator(s)
Dr. Olabimpe Genevieve BADRU
Prerequisite
-
Keywords
-

Course Description

-

INTRODUCTION TO PROBABILITY AND STATISTICS

Evaluation Tools (Active Term)

Item Type Weight (%)
Midterm Midterm 40
Quiz Quiz 10
Final Final 50
Total 100

Course outcomes

  1. 01 Apply(4) statistical methods in the engineering problem-solving approach
  2. 02 Compute(3) and interpret(3) descriptive statistics using numerical and graphical techniques
  3. 03 Identify(2) and apply(4) the basic concepts of probability
  4. 04 Apply(4) probability theory to set up tree diagrams
  5. 05 Apply(4) probability theory via Bayes’ Rule.
  6. 06 Describe(3) the properties of random variables, discrete and continuous distribution functions.
  7. 07 Identify(2) the basic concepts of joint probability distribution.

Course Syllabus

Week Topic
Week 1 Introduction
Week 2 Populations, Samples, and Processes
Week 3 Pictorial and Tabular Methods in Descriptive Statistics, Measures of Location
Week 4 Measures of Variability, Sample Space and Events
Week 5 Axioms, Interpretations and Properties of Probability, Counting Techniques
Week 6 Counting Techniques, Conditional Probability, Independence
Week 7 Definition of Random Variables, Discrete Probability Distributions
Week 8 Midterm Week
Week 9 Discrete Probability Distributions, Expected Values
Week 10 Special Discrete Prob. Distr.: Uniform, Binomial, Geometric and Poisson
Week 11 Poisson Prob. Distr., Density Functions
Week 12 Continuous Probability Distributions and Expected Values.
Week 13 Uniform Distr., Normal and Standard Normal Distr.,
Week 14 Jointly Distributed Random Variables. Expected Values.
Week 15 The Distribution of the Sample Mean and The Central Limit Theorem

Reference Books & Course Materials

  1. 01 Jay L. Devore, Probability and Statistics for Engineering and Sciences, 8th ed., Brooks/Cole Cengage Learning
  2. 02 R.E.Walpole, R.H.Myers, S.L.Myers, K.Ye, Probability and Statistics for Engineers and Scientists, 7th ed., Prentice Hall, 2002.

Learning Outcomes

  1. L01 Apply(4) statistical methods in the engineering problem-solving approach
  2. L02 Compute(3) and interpret(3) descriptive statistics using numerical and graphical techniques
  3. L03 Identify(2) and apply(4) the basic concepts of probability
  4. L04 Apply(4) probability theory to set up tree diagrams
  5. L05 Apply(4) probability theory via Bayes’ Rule.
  6. L06 Describe(3) the properties of random variables, discrete and continuous distribution functions.
  7. L07 Identify(2) the basic concepts of joint probability distribution.

Program Outcomes

No program outcomes have been defined.

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