MGTE 11023


Status : Core Pre-requisite : G.C.E. (A/L) Co-requisite : None


On completion of this course, the student should be able to:

  • Apply a variety of methods for exploring, summarizing and presenting data
  • Apply statistical modelling and analysis techniques to a wide range of practical problems
  • Evaluate statistical evidence; interpret the results of a statistical analysis
  • Develop skills in making inferences within the business environment
  • Demonstrate an understanding of PHStat data analysis software to solve selected statistical problems
  • Use R programming environment for data analysis and graphics.

Descriptive statistics: Compilation, classification, tabulation and diagrammatic and graphical representation of various types of statistical data, skewness and kurtosis, frequency distributions, and measures of location and dispersion.

Elements of Probability Theory: Set theory, concepts of probability, sample space, field of events and generalized addition theorem, conditional probability, independence, Bayes’ theorem, random variables, distribution theory, expectation, variance, normal, exponential, Binomial and Poisson Distributions.

Sampling Distribution: Population parameters and statistics, type of samples, probability distribution of sample means, distribution of linear combination of random variables and the Central Limit Theorem.

Hypothesis Testing and Confidence Intervals.

Regression Theory: Simple Linear Regression Model and Least Square Method of estimating the parameters.

Time Series and Forecasting: Secular trend, linear trend and nonlinear trend.

R-Programming: an effective data handling and storage facility, operators for calculations on array, intermediate tools for data analysis, graphical facilities for data analysis and display.

Lectures, interactive classroom sessions, case discussions, and applications of Microsoft Excel and PHStat statistical software package.

End of course unit examination, group assignments, mid-term examination, class attendance.

  1. Levine, D M, Stephan, D, Krehbiel, T C and Berenson, M L (2011). Statistics for managers: using Microsoft Excel.Prentice Hall
  2. Lind, D, Marchal, W G and Wathen, S (2011). Statistical Techniques in Business and Economics. McGraw-Hill
  3. Anderson,D R, Sweeney,D Jand Williams, T A (2010). Statistics for Business and Economics. South-Western College Pub
  4. Jared P. L (2014). R for everyone: Advanced analytics and graphics, Addision-Wesley.