Objectives and Outcomes
Course Objectives
To introduce students to the depths and richness of the Indian culture and knowledge traditions, and to enable them to obtain a synoptic view of the grandiose achievements of India in diverse fields. To equip students with a knowledge of their country and its eternal values.
Course Outcomes
CO1: Increase student understanding of true essence of India’s cultural and spiritual heritage. Emancipating Indian histories and practices from manipulation, misunderstandings, and other ideological baggage thus, shows its contemporary relevance.
CO2: Understand the ethical and political strategic concepts to induce critical approach to various theories about India.
CO3: Familiarize students with the multidimension of man’s interaction with nature, fellow beings and society in general.
CO4: Appreciate the socio-political and strategic innovations based on Indian knowledge systems. Gives an understanding of bringing Indian teaching into practical life.
CO-PO Mapping
|
PO/PSO
|
PO1 |
PO2 |
PO3 |
PO4 |
PO5 |
PO6 |
PO7 |
PO8 |
PO9 |
PO10 |
PO11 |
PO12 |
PSO1 |
PSO2 |
PSO3 |
| CO |
| CO1 |
3 |
1 |
1 |
– |
– |
– |
–
|
1 |
1 |
1 |
– |
– |
– |
– |
– |
| CO2 |
3 |
1 |
1 |
– |
– |
– |
– |
1 |
1 |
1 |
– |
– |
– |
– |
– |
| CO3 |
3 |
2 |
1 |
– |
– |
– |
– |
1 |
1 |
1 |
– |
– |
– |
– |
– |
| CO4 |
3 |
2 |
1 |
– |
– |
– |
– |
1 |
1 |
1 |
– |
– |
– |
– |
– |
Evaluation Pattern
Evaluation Pattern: 50:50
| Assessment |
Internal |
External |
| CA |
30 |
|
| Mid-semester |
30 |
|
| End Semester |
|
40
|
Text Books / References
Textbook(s)
Douglas C. Montgomery and George C. Runger, “Applied Statistics and Probability for Engineers”, (2005) John Wiley and Sons Inc.
Papoulis, and Unnikrishna Pillai, “Probability, Random Variables and Stochastic Processes”, Fourth Edition, McGraw Hill, 2002.
Reference(s)
Ravichandran, “Probability and Random Processes for Engineers”, First Edition, IK International, 2015.
Scott L. Miller, Donald G. Childers, “Probability and Random Processes”, Academic press, 2012.
Lab Experiments:
- Finding statistical measures like mean, variance, standard deviation, mode and moments for given data
- Use of ‘pdf’,’cdf’,’icdf’ commands for finding probabilities if random variable follows Binomial, Poisson, uniform exponential and normal distributions
- Generation of sample data from populations with various discrete distributions
- Generation of sample data from populations with various continuous distributions
- Multilinear Regression
- Evaluation of Covariance and Correlation using excel/MATLAB
- Multinomial and multinormal distributions
- Generation of Multivariate Data
