National University of Sciences and Technology
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STAT-835 Probability & Statistics
Campus SCEE (NIT)
Programs PG
Session Fall Semester 2016
Course Title Probability & Statistics
Course Code STAT-835
Credit Hours 3
Pre-Requisutes
Course Objectives Course Objectives:     This course is designed to equip the students with a working knowledge of probability, statistics, and modeling in the presence of uncertainties. The major objective of the course is to help the students to develop an intuition and an interest for random phenomena, and to introduce both theoretical issues and applications that may be useful in real life.

Course Outcomes: On completion of this course successful students will be able to:-
  • understand the concept of both univariate and multivariate random variables.
  • evaluate the distribution of functions of random variables and calculate expectations.
  • understand the concept of hypothesis testing.
Detail Content
  1. Decommentive Statistics
  2. Probability
  3. Hypotheses Tests
  4. Regression and Statistical Modeling
Text/Ref Books
  1. Textbooks a. Probability and Statistics For Engineering and Sciences by Jay L. Devore (6th Edition) (Available in NIT Library) b. Applied Linear Statistical Models, by Michael Kutner, Christopher Nachtsheim, John Nether, and William Li. (5th Edition) (Available in NIT Library)
  2. References
    1. Dixon, W. J. and Massey, F. J. Introduction to Statistical Analysis, 4th ed. New York: McGraw-Hill, 1983.
    2. Everitt, B. Chance Rules: An Informal Guide to Probability, Risk, and Statistics. Copernicus, 1999.
    3. Feller, W. An Introduction to Probability Theory and Its Applications, Vol. 1, 3rd ed. New York: Wiley, 1968.
    4. Fisher, N. I.; Lewis, T.; and Embleton, B. J. J. Statistical Analysis of Spherical Data. Cambridge, England: Cambridge University Press, 1987.
    5. Fisher, R. A. and Prance, G. T. The Design of Experiments, 9th ed. rev. New York: Hafner, 1974.
    6. Keeping, E. S. Introduction to Statistical Inference. New York: Dover, 1995.
    7. Mises, R. von Probability, Statistics, and Truth, 2nd rev. English ed. New York: Dover, 1981.
    8. O'Hagan, A. Kendall's Advanced Theory of Statistics, Vol. 2B: Bayesian Inference, 6th ed. New York: Oxford University Press, 1998.
    9. Ostle, B. Statistics in Research: Basic Concepts and Techniques for Research Workers, 4th ed. Ames, IA: Iowa State University Press, 1988.
    10. Papoulis, A. Probability, Random Variables, and Stochastic Processes, 2nd ed. New York: McGraw-Hill, 1984.
    11. Press, W. H.; Flannery, B. P.; Teukolsky, S. A.; and Vetterling, W. T. "Statistical Decommention of Data." Ch. 14 in Numerical Recipes in FORTRAN: The Art of Scientific Computing, 2nd ed. Cambridge, England: Cambridge University Press, pp. 603-649, 1992.
    12. Ross, S. M. A First Course in Probability, 5th ed. Englewood Cliffs, NJ: Prentice-Hall, 1997.
    13. Ross, S. M. Applied Probability Models with Optimization Applications. New York: Dover, 1992.
    14. Ross, S. M. Introduction to Probability Models, 6th ed. New York: Academic Press, 1997.
    15. Spiegel, M. R. and Stephens, L. J. Theory and Problems of Statistics, 3rd ed. New York: McGraw-Hill, 1998.
    16. Stuart, A.; and Ord, J. K. Kendall's Advanced Theory of Statistics, Vol. 1: Distribution Theory, 6th ed. New York: Oxford University Press, 1998.
    17. Stuart, A.; and Ord, J. K. Kendall's Advanced Theory of Statistics, Vol. 2A: Classical Inference & the Linear Model, 6th ed. New York: Oxford University Press, 1999.
    18. Székely, G. J. Paradoxes in Probability Theory and Mathematical Statistics, rev. ed. Dordrecht, Netherlands: Reidel, 1986.
Time Schedule Fall Semester 2015
Faculty/Resource Person Dr. Muhammad Bilal Khurshid
PhD, Purdue University, USA
Discipline: Civil Engineering
Specialty: Transportation Engineering