COURSE SUMMARY
Course Title: 
Statistical and Probabilistic Modeling in Civil Engineering
Course Code: 
18SC724
Year Taught: 
2019
Degree: 
Postgraduate (PG)
School: 
School of Engineering
Campus: 
Coimbatore

'Statistical and Probabilistic Modeling in Civil Engineering' is an elective course offered in M. Tech. program in Structural & Construction Engineering at the School of Engineering, Amrita Vishwa Vidyapeetham, Coimbatore campus.

The Role of Statistics and Probability in Civil Engineering, Elements of Probability theory: random variables, random events, Bayes theorem, Common Probabilistic models: models for Simple discrete random trails, Random occurrences and Limiting cases; Modeling of Observed data and Estimation of model parameters -Maximum likely hood, K-means; Probabilistic Models for Civil Engineering problems.

Numerical Modeling and Descriptive statistics, Hypothesis testing for civil engineering studies -Significance level, Tests Concerning the Mean of a Normal Population, Variance of a Normal Population, Equality of means of Two Normal Populations, Case of Unknown and Unequal Variances, Hypothesis Tests, The Paired t-Test, Normal Population, Null and Alternate Hypothesis,Interval Estimation and Selection of Training data.

Sample size estimation and Field data training for civil engineering studies, Sampling distribution and Point estimation of parameter,Regression models -simple linear and multiple linear models, Parameter Estimation, Least Squares Estimators of the Regression Parameters, Statistical Inferences, Distribution of the Estimators, Coefficient of Determination, NSE and MSE,Real time Case studies and Applications.

  • Probability Concepts in Engineering Planning and Design, Ang A. H-S. and W. H. Tang, John Wiley & Sons, Inc., USA, 2010.
  • Probability, Random Variables and Stochastic Processes, Papoulis, A, and S. U. Pillai, McGraw-Hill, New York, USA, 2002.
  • Miller and Freund’s Probability and Statistics for Engineers, Richard A. Jonson and C. B. Gupta, Pearson Education, Inc., USA, 2005.
  • Introduction to Probability and Statistics for Engineers and Scientists, Sheldon Ross, Elsevier, USA, 2004.