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Course List

Statistics

  • Course Code :
    MST 201
  • Level :
    Undergraduate
  • Course Hours :
    3.00 Hours
  • Department :
    Faculty of Commerce & Business Administration

Instructor information :

Area of Study :

Business Statistics introduces elementary ideas of descriptive and inferential statistics and statistical models. It assumes only basic knowledge of algebra and no calculus. Emphasis is on data analysis and interpretation using spreadsheet computer software, and not on computation and actual implementation of formulas. This course discusses how to efficiently collect the data needed to answer statistical questions properly, and how to address the questions in a rational way once the data is collected.

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Statistics

Course outcomes:

a. Knowledge and Understanding:

1- Develop students’ ability to carry out a simple exploratory data analysis; and in particular, to use simple numerical and graphical methods of summarizing data.
2- Understand the basic definitions and concepts used in probability theory.
3- Using probability distributions to model the behavior of variables.

b. Intellectual Skills:

1- Understand key inferential concepts so as to have a critical insight into the appropriateness of statistical techniques.
2- Focus on presentation of results using suitable statistical software packages .

c. Professional and Practical Skills:

1- Use the Minitab and SPSS packages.
2- Deal with case studies to cover the area of Business & Economics.

d. General and Transferable Skills:

1- Self-learning through exercises and worked examples.
2- Work in group to develop technique for problem solving.

For further information :

Statistics

Course topics and contents:

Topic No. of hours Lecture Tutorial/Practical
Data Collection: Fundamental concepts of statistics, Sampling and randomization. 4 3 1
Random Variables and Probability Distributions: Discrete random variables, 4 3 1
Second Mid Term 4 3 1
Continuous random variables, Expected value 4 3 1
Binomial distribution, Normal distribution 4 3 1
Simple Linear Regression and Correlation coefficients. 4 3 1
Revision 4 3 1
Frequency distribution, Bar charts, Pie charts. 4 3 1
Histograms, Comparing distributions. 4 3 1
Contingency tables, Scatter diagrams. 4 3 1
Numerical Description of Data: Measures of central tendency. 4 3 1
First Mid Term 4 3 1
Measures of variation. 4 3 1
Shape of a data distribution, Box plots and outliers. 4 3 1
Basic Probability: Sample space and events , Basic laws of probability, Conditional probability. 4 3 1

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