• Short Name N/A
  • Course code STT 501
  • Semester First Trimester
  • Full Marks 100
  • Pass Marks 60
  • Credit Hrs 3
  • Elective/Compulsary Compulsary


Chapter wise complete Notes.

Course Description

Course Description

This course is designed to familiarize students with basic concepts in statistics. The contents include the data analysis techniques, the study of probability and measures of uncertainty, discrete and continuous distribution, estimation, hypothesis testing, correlation and regression analysis, and the application of other relevant modern statistical methods for decision-making with emphasis on business application. Throughout the course students will utilize the technology to gather, organize, and summarize the data into meaningful information. Further, students will apply the software to draw inferences from the data so that appropriate decisions can be recommended.

Unit Contents

Course Contents

         Introduction and Data Collection                               

Definition of statistics, Application in Business and Economics, Descriptive and Inferential Statistics, Types of Data (Categorical and Numerical), Classification of data (Cross-sectional, Time series, Pooled), Sources of Data (Primary and Secondary), Census and Sampling, Parameter and Statistics, Data Collection Technique, Questionnaire Construction.

         Summarization of Data           

Grouping and Displaying Data. Data array, Stem and Leaf Display, Frequency Distribution (Relative, Percentage and cumulative), Histogram (Frequency, Relative Frequency and Percentage), Frequency Polygon, Frequency Curve, Ogives, Bar Diagram, Pie Charts. Construction of Diagrams, Charts and Histogram using SPSS and their applications.

Numerical Descriptive Measures. Arithmetic Mean, Median, Mode, Midhinge, Midrange, Quartiles, Range, Standard Deviation, Variance, Coefficient of Variation, Shape (Symmetric and Skewed), Exploratory Data Analysis (Five Number Summary, Box and Whisker Plot), Application of Numerical Descriptive Measures and Analysis using SPSS.

Basic Probability: Concepts and Applications. Set Operations, Basic Concepts, Contingency Table, Simple and Joint Probability, Subjective and Objective Probability, Additive and Multiplicative Rules, Conditional Probability, Independence, Bays Theorem, Counting Rules, Application of Probability in Decision Making Process, Applications of Probability concepts and Analysis using SPSS.

         Probability Distributions                                             

Random Variable, Expectation ( Expected Value, Standard Deviation and Variance of a Discrete Random Variable),  Application of Expectation in Decision Making Process, Binomial Distribution, Poisson Distribution, Normal Distribution.

         Sampling Distribution and Estimation            

Sampling, Types of Sampling, Sampling Distribution of Mean, Sampling Distribution of Proportion, Properties of Estimation, Point Estimation, Interval Estimation (Single Mean, Single Proportion, Difference between Two Means and Difference between Two Proportions), Sample Size Determination (Mean and Proportion), Connection between Confidence Level, Sample Size and Sampling Error.

         Hypothesis Testing                                                      

Null and Alternative Hypothesis, Level of Significance, Confidence Level, Power of the Test, Type I and Type II Error, Critical Value, P-value, One and Two Tailed Test, Steps Involved in Hypothesis Testing, One Sample Test for Mean and Proportion, Two Samples Test for Mean (Independent and dependent) and Proportion.

         Chi-Square Test and Analysis of Variance                                                    

Introduction, Cross Tabulation, Chi-Square as a Test of Independence, Comparison of Three or More than Three Means (One-Way Analysis of Variance). Application of Hypothesis Testing, Chi-Square Test and Analysis of Variance using SPSS.

         Correlation and Regression Analysis                                     

Correlation coefficient, Properties, Simple Linear Regression Model, Residual Analysis, Coefficient of Determination, Standard Error.

Text and Reference Books

Basic Books

Levine, D. M., Krehbiel, T. C., Berenson, M. L., and Viswanathan, P. K.,   Business Statistics (Fourth Edition), New Delhi: Pearson Education.

Levin, R. I. and Rubin, D. S., Statistics for Management (Seventh Edition), New Delhi: Prentice Hall.


   Siegel, A. F., Practical Business Statistics (Fourth Edition), New York: Andrew F, Irwin.


   Anderson, D. R., Sweeney, D.J. and Williams, T. A., Statistics for Business and Economics (Eighth Edition), New Delhi: Thomson.