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Basic Details:

  • Course Code: EM 2050
  • Credits: 2
  • Pre-requisites: –
  • Compulsory/Optional: Compulsory

Aim :

To introduce basic concepts of probability and inferential statistics.

Intended Learning Outcomes:

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

  • Demonstrate fundamental probability and statistical concepts.
  • Apply standard discrete and continuous probability distributions and observe their role as the foundation for statistical inference.
    ● Perform estimation and testing of hypothesis on common measures in decision making.

Couse Content:

Discrete and continuous random variables, probability functions, mean, expectation and variance, moment generating functions.

Bernoulli (Point binomial) Distribution, binomial distribution, Poisson distribution, geometric distribution, hypergeometric distribution.

Uniform distribution, exponential distribution, normal distribution, Student-t distribution, Weibull distribution and Chi-square distribution.

The central limit theorem and normal approximation to the binomial distribution, sampling distribution of sample mean and sample variance.

Estimation and calculation of Confidence Intervals for mean, difference of means and variance.

Test of hypothesis for mean and difference of means.

Time Allocation (Hours):

Lectures
0
Tutorials
0
Practical Assignments
0

Recommended Texts:

  • D.C. Montgomery and G.C. Runger Applied Statistics and Probability for Engineers, 6thedition,(2013), John Wiley and SonsInc.
  • Jay L. Devore, Probability and Statistics for Engineering and the Sciences, 8thedition, (2010),Cengage Learning.

Assessment:

In - course:

Tutorials/Assignments/Quizzes
10%

Mid-semester:

30%

End-semester:

60%