Course Outline STA 240 SPRING SEMESTER 2011

IUBAT–INTERNATIONAL UNIVERSITY OF BUSINESS AGRICULTURE AND TECHNOLOGY

Course Outline Part A

College : College of Arts and Sciences Course Number: STA 240

Program: Bachelor of Science

Major: STATISTICS Course Name : Statistics

Hours/Week: 3 Total Hours: 48

Lecture : 3 Total Week: 16 Credits: 3

Course Goals

At the end of the course the students are expected to learn: a) The basic concept of statistics and statistical methods. The methods of

collection and presentation of data, the basic concepts of frequency distribution, central tendency, dispersion, estimations, appropriate tests etc.

b) On the basis of that simple statistics how to draw inference and make conclusions.

c) Moreover, they will be able to handle any survey or enquiry or investigation or research in their respective field and from the collected data they will be able to generate informations and presenting the informations in scientific way to produce or write a sensible report.

Course Description:

The course is designed to introduce to the students the basic concept and tools of statistics and enable them to relate these to real life problems. Topics include probability concepts and laws, sample spaces, random variables (discrete and continuous); binomial, poisson, uniform, normal, exponential; two-dimensional variates, expected values. Collection, processing, organization and presentation of data, frequency distribution, measure of central tendency and dispersion, confidence limits, estimation and hypothesis testing, regression, correlation, chi square and non-parametic statistics; time series. Type and source of published statistics in Bangladesh.

Evaluation 1. First Term Exam 20% 2. Mid-term Exam 20% 3. Quizzes 10% 4. Assingments 10% 5. Attendance 5% 6. Final Term Exam (Covering the entire course) 35% Total 100%

Course Outcomes and Sub-Outcomes Understand why we study statistics, organize data represent and those in a simple way, understand probability and its use in decision making, understand why a sample is often the only feasible way to learn something about a population, learn tests of hypothesis to face real life situation and familiarize one self with forecasting method.

Prior Learning Assessment Methods

Assessment methods include first-term, mid-term and final examination. There will also be announced and unannounced quizzes. Moreover, the course instructor will give assignments when he finds it appropriate.

Developed by Professor Md. Amanullah Date: 07/05/2011

Instructor Name and Department (Signature): Md. Mortuza Ahmmed Faculty, Department of Statistics College of Arts and Science


Course Outline Part B College of : College of Arts and Sciences

Program: Bachelor of Science Major: STATISTICS

Instructor : Md. Mortuza Ahmmed

Room No:322

Phone:01819178019 E-mail: [email protected]

Office Hrs: 8:30 AM - 5:00 PM. at IUBAT Campus (in Schedule date)

Councelling Hours: Sunday-Wednesday 10:30AM-12:30PM

Text(s) and Equipment

Prem S. Mann, Introductory Statistics Douglas, William and Samuel, Statistical Techniques in Business & Economics McGraw-Hill,

2005 Paul Newbold, W. L. Carlson Thorne (5th Edition), Statistics for Business and Economics Anderson and Sweeney, Statistics for Business and Economics (6th Edition) M.G Mostofa, Introduction to Mathematical Statistics, S. P. Gupta and M.P. Gupta Business Statistics (Latest Edition).

Course Notes (Policies and Procedures)

All the definition and theories will be clearly explained in the class lectures and relating problems will be solved. Students must collect these through class notes by regular attendance. Queries will be solved in the class and the task on relative chapters will be delivered during class lectures. All home works will be checked and discussed with the students. Some class tests will be setup to prepare the students for the examination.

Assignment Details

Assigment(s) will be provided in the class.


College of Arts amd Sciences (CAAS)

Summer Semester -2011 Program: Bachelor of Science Major: STATISTICS

Day Outcome/MaterialCovered Reference Reading

Assignment DueDate

Day 1

Introduction to statistics: scope of statistics

Douglas/ M.G Mostofa/ Gupta

Day 2

Statistics and Related Terms: Definitions and Examples


Day 3

Data Collection and Data Representation:Tabular Representation


Day 4

Cont. Douglas/ M.G

Mostofa/ Gupta

Day 5

Data Representation: Graphical representation of Data


Day 6

Cont. Douglas/ M.G

Mostofa/ Gupta

Day 7

Descriptive Statistics: Descriptive summary measure, Measures of Central

tendency.


Day 8

Mean, Median, Mode, GM, HM Douglas/ M.G

Mostofa/ Gupta

Day 9

Practical uses of Mean, Median, Mode, GM, HM.


Day 10

Absolute and relative Measures of Dispersion.


Day 11

Uses of absolute and relative Measures of Dispersion.


Day 12

Skewness and Kurtosis, Moments and Descriptive Statistics.


Day 13 Review

Day 14

Simple Correlation: Types of relationships, Scatter diagram,

Coefficient of correlation, Co-efficient of determination.


Day 15

Properties of correlation. Uses and misuses or abuses of correlation.


Day 16

Interpretation of findings associated with correlation.


First term examination begins from Jun-3 and must end by Jun 10, 2011

Day 17 Simple Regression analysis. Estmation Douglas/ M.G

of Coefficient of regression, Drawing the regression line and Co-efficient of

determination.

Mostofa/ Gupta

Day 18

Properties of regression. Uses and misuses or abuses of regression.

Douglas/ M.G

Mostofa/ Gupta

Day 19

Interpretation of findings associated with regression.

Douglas/ M.G

Mostofa/ Gupta

Day 20

Introduction to Probability, classical, empirical, and subjective approaches to

Probability. Douglas/ M.G

Mostofa/ Gupta

Day 21

Conditional probability and joint probability. Some rules for calculating

probabilities.


Day 22

Application of a tree diagram to organize and compute probabilities.


Day 23

Discrite Probability Distributions and its some of the properties.


Day 24

Practical examples of Discrite Probability Distribution.


Day 25

Continuous Probability Distributions and its some of the properties.

Douglas/ M.G

Mostofa/ Gupta

Day 26

Practical examples of Continuous Probability Distribution.

Douglas/ M.G

Mostofa/ Gupta

Day 27

Review

Day 28

Sampling Methods and Central limit Theorem

Douglas/ M.G

Mostofa/ Gupta

Day 29

Defination of Hypothesis, Null Hypothesis, Alternative Hypothesis, Procedure for Tesing Hypothesis.

Douglas/ M.G

Mostofa/ Gupta

Day 30

One-tail Test, Two-tail Test, Type one Error, Type Two Error and Power of

the Test.

Douglas/ M.G

Mostofa/ Gupta

Day 31

Hypothesis testing, Z-test and t-test. Douglas/ M.G

Mostofa/ Gupta

Day 32 Hypothesis testing, F- test and χ2-test.


Mid Term Examination begins from July 03 and must end by July 11, 2011.

Day 33

Simple Index Numbers, Construction of Index

Numbers Douglas/ M.G

Mostofa/ Gupta

Day 34

Unweighted Indexes: Simple Average of the Price Index, Simple Aggregate Index


Day 35

Weighted Indexes: Laspeyres Price Index, Paasche Price Index and Fishers’s Price

Index.


Day 36

Value Index and Consumer Price Index. Douglas/ M.G

Mostofa/ Gupta

Day 37

Introduction to Time series and Forecasting

Douglas Laurence

Day 38

Components of a Time Series: Secular Trend, Cyclical Variation, Seasonal

Variation, Irregular Variation. Douglas Laurence

Day 39

A Moving Average, Weighted Moving Average.

Douglas Laurence

Day 40

Linear Trend and Forecasting. Douglas Laurence

Day 41

Practical examples of Time series and Forecasting.

Douglas Laurence

Day 42

Review

Final Examination as per scheduled declared by Registry.

Documents

Course Outline STA 240 SPRING SEMESTER 2011