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 The course content includes: types of data, frequency distributions, measures of central tendency and dispersion, exploratory data analysis, introduction.

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Presentation on theme: " The course content includes: types of data, frequency distributions, measures of central tendency and dispersion, exploratory data analysis, introduction."— Presentation transcript:


2  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 and continuous random variables, Binomial distribution, Poisson distribution, Normal distribution, index numbers and time series analysis.(IBA prog. Ann. 2009-10). This course will also introduce the use of statistical soft ware packages like SPSS and MINITAB for data inputting, exploration and data analysis.


4 A. Introductory Statistics by Neil A.Weiss 4 th or 5 th Edition B. Introduction to Statistics by Ronald A. Walpole 3 rd edition C. Introduction to Statistical Theory Part 1 by Prof. Sher M. Choudhry and Dr. Shahid Kamal

5 Hand outs Articles Visual aids like White board Multi media presentations and demos Overhead projector slides Small class room activities


7 What is Statistics?; Descriptive and Inferential Statistics; Significance of statistics and application of Statistics in key functional areas of business; Introduction to key terms; Methods of Sampling TITLECHAPTER(S)SESSION(S) Nature of Statistics A11-2

8 Types of variables; Types of data; Organization and graphical presentation of discrete and continuous data; TITLECHAPTER(S)SESSION(S) Descriptive Statistics A2, B3.1, B3.2 2-4

9 Measures of central tendency and dispersion for grouped and ungrouped data; Chebyshev theorem; Z-Scores; Quantiles; Outliers; Exploratory data analysis. TITLECHAPTER(S)SESSION(S) Descriptive Measures A3, B2, B3.3,B3.4 5-8

10 Sets; Events and relationship between events; laws of probability; Conditional and marginal probability; independent and dependent events; Mutually exclusive and exhaustive events; Total probability and Bayes Theorem; Counting techniques; application of counting techniques to the probability. TITLECHAPTER(S)SESSION(S) Probability Concepts A4, B49-12

11 Random variables; mean and variance of random variable; discrete and continuous random variables; Binomial distribution; Poisson distribution; Poisson approximation to binomial distribution; mean and variance of binomial and Poisson distribution TITLECHAPTER(S)SESSION(S) Discrete Random Variables A513-15

12 Normal random variable; normal probability plots; standard normal distribution; normal approximation to binomial distribution TITLECHAPTER(S)SESSION(S) Normal Distribution A616-17

13 Simple linear regression; scatter diagram; error sum of square, regression sum of square ; coefficient of determination and coefficient of correlation TITLECHAPTER(S)SESSION(S) Descriptive Methods in Regression and Correlation A13.1,A13.2, A13.3,A13.4,C10 18-20

14 Simple and aggregative price indices; weighted price indices; weighted aggregative indices (Laspeyers price index, Paasches price index, Fishers Ideal price index); Consumer Price Index (CPI),; Applications of CPI; CPI computation methodology in Pakistan TITLECHAPTER(S)SESSION(S) Index Numbers C5; Handouts21-23

15 Decomposition of time series using the multiplicative model; Seasonally adjusted values; Forecasting TITLECHAPTER(S)SESSION(S) Time Series Analysis Handouts24-26

16 TITLECHAPTER(S)SESSION(S) Introduction to Minitab and SPSS Handouts and lab 27-28 Entering the data; exploring and summarizing the data; modifying the data; data analysis

17 Quizzes10 marks ( best n-1) Assignments10 (weighted average of all the assignments) Term Examinations40 Final Examination40 Total100

18  Each quiz will carry 3.33 marks and the final grade will be averaged out of 10 points.  Generally, the class will be divided into odd and even columns. Separate quizzes will be given to the odd column students and even column students in order to ensure that no unfair means are used by the students.  Some of the quizzes shall be pre-announced and some will be taken at a random surprise basis to test the student’s understanding and comprehension of the previous lectures, assignments or advance assignments of reading.  Students are requested to read and understand the discipline rules given in the program prospectus regarding the use of unfair means in assignments/quizzes/examination.  Quiz duration approx= 10-15 mins

19 1. All the assignments shall be graded and a weighted average grade will be awarded to the students for the assignments. 2. Each assignment shall be graded according to the following grid: -++ A9.09.59.810.0 B8.08.58.8 C7.07.57.8 D6.06.56.8

20 3. An ‘F” is a ‘0’. 4. Any assignment submitted after the due date shall not be accepted for grading. If any assignment is found to be copied then the respective student(s) shall be awarded with an ‘F” in the respective assignment. 5. The final grade of all the assignments shall be computed as follows: Suppose student X was given 5 assignments during the course in a semester. Student X submitted all the 5 assignments on time to the teacher for grading. The graded assignments were given the following grades: A++, A-, B, C+, and D.

21 A++10.00 A-9.00 B8.50 C+7.80 D6.50 Total of All X Assignments41.80 Total of All Assignments50.00 Percentage0.836 total points for each assignment10.00 % age * total points for each assignment8.36 Final grade8.36

22 (for global data) (for national data)

23  Monday and Thursday by appointment


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