After completion of this course each student would be able to:
The Industrial Probability & Estimations is a compulsory course and has been offered by the Department of Industrial Engineering and Management.
|
CLOs |
Description |
Taxonomy Level |
PLO |
|
1 |
SUMMARISE the main features of a data set (descriptive data analysis) |
C2 |
2 |
|
2 |
REVIEW the basic principles of probability including the Laws and use these principles in problem solving situations. |
C2 |
2 |
|
3 |
ANALYZE statistical hypotheses. |
C4 |
4 |
Practical/Lab work
|
CLO |
Description |
Taxonomy Level |
PLO |
|
1 |
ADOPT general and specific safety guidelines during lab work. |
A3 |
6 |
|
2 |
PERFORM the different analysis related to probability & estimations. |
P4 |
5 |
|
3 |
CONDUCT open-ended lab work within the scope of industrial probability & estimations. |
P4 |
12 |
|
4 |
RESPOND to different situations related to subject and must express opinion regarding a problem. |
A2 |
4 |
Course Contents:
Introduction to Descriptive and inferential statistics, Counting techniques, dependent and independent events, conditional probability, Additive rules of Probability. Contingency tables, joint and marginal probabilities, the multiplication rule, Bayes’s theorem.
Introduction to central tendency and dispersion, Grouped data, Un-grouped data, Types of averages, Importance of measure of dispersion, classification of measure of dispersion.
Concept of Random variables, Discrete and continuous probability distribution, Mean and variance of a random variable. Binomial and Poisson distributions, mean and variance of Binomial and Poisson distribution, Normal distribution, Standard normal distribution and inverse use of table of areas under normal curve.
Methods of Sampling, Sampling distribution of means with and without replacement, central limit theorem.
Types of estimations, estimating confidence interval of one population mean, estimating the difference between two population means, chi-square distribution.
Testing a statistical hypothesis, types I & II error, one tailed and two tailed tests. Test concerning means and variances, testing the difference between two means, Good-ness of fit test.
Concept of regression and correlation, Types of Correlation, Co-efficient of correlation, Co-efficient of determination, Simple and multiple regression, Simple regression analysis.
Note: Labs will be based on Theory
