CENG 222

Probability and Statistics

Elementary probability theory, conditional probability and independence, random variables, distribution functions, joint and conditional distributions, law of large numbers, central limit theorem, parameter estimation, confidence intervals, and hypothesis testing.

Learning Outcomes:

1.To be able to explain and apply the concepts of probability and random variables.
2.To be able to describe and use common probability distributions and their properties.
3.To be able to employ descriptive statistics.
4.To be able to estimate distribution parameters.
5.To be able to calculate confidence intervals.
6.To be able to conduct hypothesis testing.
7.To be able to utilize computation as a tool to explore concepts in probability and statistics and to do quantitative analysis.

Population and Variates, Tables and Graphs, the Center of a Set of Observations
The Measure of Variability, Samples and Population
Random Variables, Expectation of a Random Variable
Discrete Random Variables, Uniform, Bernoulli, Binomial and Poisson Distibutions
Continuous Random Variables, Normal Distribution
Testing Hypotheses
Testing Hypotheses, Large Sample Tests
Testing Hypotheses, Small Sample Tests
Testing Hypotheses Using X^2 Distibution
Linear Regression and Correlation


Lecturer Dr.
Assistant Professor / Vice Chair