Introduction to Statistics (MTS-102) Course Outline Review Introduction to Statistics (MTS-102) BBA-II, BS, BBA (exec) Spring Semester - 2009 Instructors: Ms. Aniqa Kashif, Dr. Musarrat A. Khan, Ms. Rubina Sethi & Mr. Yaseen Ahmed Meenai

Course Description: The course content includes; types of data, frequency distributions, measures of central tendency and dispersion, exploratory data analysis, introduction to set and probability theory, events and laws of probability, independence, conditional probability, discrete random variables, Binomial and Poisson distributions, index numbers and time series (IBA prog. Ann. 2008-09) Prerequisites: Business Maths, Remedial College Algebra

Recommended Text & Ref. Books: Neil A. Weiss; Introductory Statistics, Addison Wesley (5th Edition) Ronald E. Walpole (3rd. Ed.); Elements of Statistics & Probability ___________________________ Handouts by the instructor

Grading Plan 1. 3 quizzes (will consider best of 2) 10 marks 2. 2 Hourly/Term Exams 40 marks 3. Term Report (Based on projects & case studies) 4. Home assignments 5. Final Examination 30 marks 100 marks (total)

Course Outline Chapter 1 : Presentation of Data Introduction, Types of Data, Quantitative, Qualitative Data. Tabulation of Data, frequency distributions, Intervals, limits and boundaries. Graphical Presentation, Bar Charts and histograms, Frequency polygons, Pie diagrams Sessions required? _____

Course Outline Chapter 2 : Statistical Measures Introduction and Notation, variable and summation notation. The Arithmetic mean, for a set, for a frequency distribution, the method of coding. The Median, mode and the geometric mean, quantiles, Elementary measures of dispersion. The range, mean deviation, standard deviation & variance. Exploratory Data Analysis, Moments and measures of skewness & kurtosis Sessions required? _____

Course Outline Chapter 3 : Probability Introduction, Elementary set theory, Experiments and Events, types of Events, Elementary probability. Conditional Probability & Independence, Baye’s Theorem Sessions required? _____

Course Outline Chapter 4 : Random Variables Discrete Random variables, Density functions. A probability distribution. Mathematical Expectation, properties of the operator ‘E’, variance of random variable ‘X’, moments of probability distribution, moment generating function (MGF) Sessions required? _____

Course Outline Chapter 5 : Some special probability distributions Introduction, related mathematics. The Binomial distribution, Poisson distribution, mean and variance of Binomial & Poisson distributions Sessions required? _____

Course Outline Chapter 6 : Time Series & Index Numbers Introduction, components of the time series, multiplicative & additive models. The trend exploration techniques, semi average technique, moving averages, method of least squares.Index numbers, price relatives, simple and multiple index numbers, value index, Laspeyre’s , Paasche’s and Fisher index Sessions required? _____

Course Outline Computer Lab sessions Introduction to MINITAB & SPSS (statistical packages), computing measures by using commands & MACRO programming

Thankyou 