Statistics and Probability (MTCE2072)

Pre-requisite(s)

None

Recommended Book(s)

Statistical Methods For Engineer, McCuen R. P. H., Latest Edition

                                                 

Reference Book(s)

Basic Statics For Business & Economics, Doughlas A Lind, Latest Edition

Course Objectives

1. To learn and perform statistical analysis of data related to civil engineering research and projects. 2. To learn and perform probability analysis of data related to civil engineering research and projects.

Course Learning Outcomes (CLO)

CLO:1            Learn and perform statistical analysis of data related to civil engineering research and projects.   

CLO:2            Learn and perform probability analysis of data related to civil engineering research and projects.

CLO:3            Be able to use soft wares i.e. Microsoft excel, Microsoft access and Matlab for complex problems having huge data.

Course Contents

Presentation of Data and Measures of Central Tendency

  • Classification, tabulation, classes, graphical representation, histograms, frequency polygons, frequency curves and their types

  • Means: Arithmetic Mean (A.M), Geometric Mean (GM), Harmonic Mean (HM), and their properties, Weighted mean, median, quartiles, mode and their relations, Merits and demerits of Averages

Measures of Dispersion

  • Range, moments, skewness, quartile deviation

  • Mean deviation

  • Standard deviation

  • Variance and its coefficients, kurtosis

Curve Fitting and Simple Regression

  • Goodness of fit

  • Fitting a straight line, parabola, circle

  • Scatter diagram

  • Linear regression and correlation

Probability and Random Variable

  • Definitions, sample space, events.

  • Laws of probability, conditional probability

  • Dependent and independent events

Probability Distribution

  • Introduction, distribution function, discrete random variable and its probability distribution

  • Continuous random variable and its probability density function

  • Mathematical expectation of a random variable

  • Moment generating functions

  • Binomial, Poisson, uniform, exponential and normal distribution functions and its approximation to Poisson distribution

Use of Soft wares

  • Microsoft Excel

  • Microsoft Access

  • Matlab

 

 

Mapping of CLOs to Program Learning Outcomes

CLO’s

CLO-1

 (Learn and Perform Statistical Analysis)

CLO-2

(Learn and Perform Probability Analysis)

CLO-3

(Use of Softwares)

PLO’s

PLO-1

(Engineering Knowledge)

 

 

 

PLO-2

(Problem Analysis)

 

PLO-3

(Design/Development of Solutions)

 

 

 

PLO-4

(Investigation)

 

 

 

PLO-5

(Modern Tool Usage)

 

 

PLO-6

(The Engineer and Society)

 

 

 

PLO-7

(Environment and Sustainability)

 

 

 

PLO-8

(Ethics)

 

 

 

PLO-9

(Individual and Team work)

 

 

 

PLO-10

(Communication)

 

 

 

PLO-11

(Project Management)

 

 

 

PLO-12

(Lifelong Learning)

 

 

 

Mapping of CLOs to Assessment Modules

CLOs

CLO:1

CLO:2

CLO:3

Assessment Modules

Assignments (20-25%)

 

Quizzes (15-20%)

Midterm Exam (20%)

 

 

Final Exam (40-45%)