Annexure ‘CD – 01’
FORMAT FOR COURSE CURRICULUM
Course Title: BUSINESS STATISTICS
Credit Units: 03
Course Level: UG
L
T
P/S
SW/FW
No. of
PSDA
TOTAL
CREDIT
UNITS
3
-
-
-
2
3
Course Code: QAM 103
Course Objectives: The objective of this course is to familiarize the students with fundamental statistical tools which can help them in analyzing the
business data. This course will provide students with hands-on experience to use statistical tools in order to make scientific decisions even in
uncertain business environment
Pre-requisites: The students should have basic knowledge of Mathematics and computational skill.
Course Contents/Syllabus:
Course Contents/Syllabus:
Module I: Introduction to Statistics
▪ Definitions, Functions of Statistics, Limitation of Statistics, Applications of Statistics
▪ Collection of Data: Types and Methods, Classification and Presentation of data: Histogram, Frequency
Curve, Frequency Polygon, Ogive
Module II: Measure of Central Tendency
▪ Concepts of Central Tendency: Meaning and Characteristics of Average
▪ Types of Averages: Arithmetic mean; Combined mean; Weighted mean; Median; Mode
Module III : Measure of Dispersion
▪ Measures of Dispersion: Range, Quartile Deviation, Mean Deviation, Standard Deviation,
Combined
Standard Deviation, Correct Incorrect Values,
▪ Coefficient of Variation (Absolute & Relative Measure of Dispersion),
▪ Skewness-Karl-Pearson’s Coefficient of Skewness, Bowley’s Coefficient of Skewness, Moments,
Kurtosis.
Module IV : Correlation Analysis and Regression Analysis
Correlation:
▪ Introduction-Importance of Correlation, Types of Correlation,
Weightage (%)
10%
20%
20%
20%
▪ Scatter Diagram Method,
▪ Karl Pearson’s coefficient of Correlation (Grouped and Ungrouped),
▪ Spearman’s Coefficient of Rank Correlation, Rank Correlation for Tied Ranks,
Regression Analysis:
▪ Concepts of Regression, Difference b/w Correlation and Regression,
▪ Regression Lines. Regression Coefficient in a bi-variate frequency
Module V Time Series Analysis
▪ Introduction; Objectives of Time Series analysis;
▪ Components of a Time Series;
▪ Moving Average Method; method of least squares (fitting of linear trend only)
Module V1 Probability Theory and Distributions
▪ Concept; Addition and multiplication theorems of probability; conditional probability & independent
events;
▪ Bayes’ theorem; Probability Distribution Function, Binomial distribution; Poisson distribution; Normal
distribution and their applications
10%
20%
Course Learning Outcomes:
On completion of this course the student will be able to:
CLO1: Remember fundamental tools and techniques of Descriptive Statistics.
CLO2: Understand and identify statistical tools relevant for data summarization, visualization and presentation.
CLO3: Apply statistical tools and techniques for developing skill of computation and solving business problems.
CLO4: Analyze and interpret result for making effective business decisions.
CLO5: Evaluation of uncertainty using probability theory.
CLO 6: Create statistical models for forecasting.
Mapping of Course learning outcomes (CLOs) with Graduate Attributes (GA)
Course Learning Outcomes
Graduate Attributes
Knowledge and Expertise of Business Analytics
Self-directed and Active learning
CLO1
CLO2
CLO3
CLO4
CLO5
CLO6
Research and Enquiry
Information & Communication Technology Skills
Critical thinking and Problem-Solving Abilities
Communication Skills
Creativity, Innovation & Reflective Thinking
Analytical & Decision-Making Ability
Leadership & Teamwork
Multicultural Understanding & Global Outlook
Integrity and Ethics
Social & Emotional Skills
Employability, Enterprise & Entrepreneurship
Pedagogy for Course Delivery: The course pedagogy will include four quadrant approach, discussion on numerical applications, computational practice
through Ms-Excel .
List of Professional Skill Development Activities (PSDA):
i. Presentation of a secondary data by various data visualization tool using Ms Excel and interpretation.
ii. Term paper on application of statistical tools to describe any secondary data and interpret the result.
Assessment/ Examination Scheme:
Theory L/T (%)
100
Theory Assessment (L&T):
Lab/Practical/Studio (%)
Components (Drop
down)
Mid Term Exam
Linkage of PSDA with
Internal Assessment
Component, if any
Weightage (%)
Continuous Assessment/Internal Assessment
(50 %)
Home Assignment
Presentation
Term Paper
15
PSDA1
PSDA2
10
10
10
Mapping Continuous Evaluationcomponents/PSDA with CLOs
Bloom’s Level >
Course Learning
Outcomes
Assessment
type/PSDA
Mid Term Exam
Home Assignment
Presentation(PSDA1)
Term Paper(PSDA2)
Remembering
CLO1
Understanding
CLO2
✓
✓
✓
✓
✓
✓
✓
Applying Analysing Evaluating Creating
CLO3 CLO4
CLO5 CLO 6
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Text Reading:
• Sharma J K (2014), Fundamentals of Business Statistics, Vikas Pub. House 2. Gupta S P (2013),
Statistical Methods, S. Chand & Co.
• Kapoor & Sancheti,(2011), Business Statistics, Sultan Chand & Sons
References:
•
Anderson Sweeney Williams(2010), Statistics for Business and Economics, Eighth edition, Thomson
•
Rubin & Levin (2013), Statistics for Management, Seventh edition, Pearson, Prentice Hall of India.
Any other Study Material:
•
Levine D.M.,David F. Stephan,Kathryn A. Szabat( 2017), Statistics for Managers Using Microsoft Excel, Eighth edition, Pearson
End Term Examination
(50%)
Attendance
5
50