Back

Probability and Statistics - EM213

Credits : 2

Prerequisites : –

Compulsory/Optional : Compulsory

Aim(s)
To introduce basic concepts of probability and inferential statistics.
Intended Learning Outcomes

On successful completion of the course, the students should be able to;

  1. Demonstrate fundamental probability and statistical concepts.
  2. Apply standard discrete and continuous probability distributions and observe their role as the foundation for statistical inference.
  3. Perform estimation and testing of hypothesis on common measures in decision making.
Course content/Course description
  1. Concepts of probability:Discrete and continuous random variables, probability functions, mean, expectation and variance, moment generating functions.
  2. Discrete probability distributions: Bernoulli (Point binomial) Distribution, binomial distribution, Poisson distribution, geometric distribution, hypergeometric distribution.
  3. Continuous probability distributions: Uniform distribution, exponential distribution, normal distribution, Student-t distribution, Weibull distribution and Chi-square distribution.
  4. Sampling distributions:The central limit theorem and normal approximation to the binomial distribution, sampling distribution of sample mean and sample variance.
  5. Estimation and Confidence Intervals: Estimation and calculation of Confidence Intervals for mean, difference of means and variance.
  6. Test of Hypothesis (3): Test of hypothesis for mean and difference of means.
Recommended Texts
  1. D.C. Montgomery and G.C. Runger Applied Statistics and Probability for Engineers, 6thedition,(2013), John Wiley and SonsInc.
  2. Jay L. Devore, Probability and Statistics for Engineering and the Sciences, 8th edition, (2010),Cengage Learning.
Time AllocationHours
Lectures24
Tutorials4
Practical
Assignments4
 
AssessmentPercentage Marks
In-course
Tutorials10
Mid Semester Examination30
End-semester60