[vc_row el_class=”inner-body-content” css=”.vc_custom_1668486569150{padding-top: 30px !important;padding-bottom: 20px !important;}”][vc_column][vc_custom_heading text=”COURSE OBJECTIVES” use_theme_fonts=”yes” css=”.vc_custom_1668486539485{margin-top: 0px !important;}”][vc_column_text]

[/vc_column_text][vc_custom_heading text=”COURSE LEARNING OUTCOMES (CLO)” font_container=”tag:h3|text_align:left” use_theme_fonts=”yes”][vc_column_text]CLO: 1. To explain the use of descriptive techniques to describe the statistical data.
CLO: 2. to solve statistical problems in engineering by sciences using concepts and methods of probability theory.
CLO: 3. to clarify the analysis of civil engineering problem solved by statistical methods.
CLO: 4. to use statistical tools (MS Excel and Mat Lab) for the presentation of the statistical data.
[/vc_column_text][vc_custom_heading text=”COURSE CONTENTS” use_theme_fonts=”yes”][vc_column_text css=”.vc_custom_1668486526452{margin-bottom: 0px !important;}”]

  1. Presentation of Data and Measures of Central Tendency
    • Classification, tabulation, classes, graphical representation, histograms, frequency polygons, frequency curves and their types
    • _Arithmetic Mean (A.M), Geometric Mean (GM), Weighted mean, median,quartiles, mode and their relations, Merits and demerits of Averages
  2. Measures of Dispersion
    • Range, moments, skewness, quartile deviation
    • Mean deviation
    • Standard deviation
    • Variance and its coefficients
  3. Curve Fitting and Simple Regression
    • Goodness of fit
    • Scatter diagram
    • Fitting a straight line
    • Linear regression and correlation
  4. Probability and Random Variable
    • Definitions, sample space, events
    • Laws of probability, conditional probability
    • Dependent and independent events
  5. Probability Distribution
    • Introduction, distribution function
    • Discrete random variable and its probability distribution (Binomial, Poisson)
    • Continuous random variable and its probability density function, uniform, and normal distribution functions
    • Mathematical expectation of a random variable
  6. Introduction to Softwares
    • Microsoft Excel
    • Matlab