1. FOOD AND AGRI BUSINESS SCHOOL, HYDERABAD
PGDM (Agribusiness) - 2015-17
Term I: Business Mathematics and Statistics
Credits: 6 No. of sessions: 30
Course Objective:
Managers today face a daunting task in their professional life to solve business problems for meeting
the objectives. Managers usually come across huge data and at times business scenario in the
organization makes analysis more complex. Statistical tools often have proved to be of immense help
for the manager in this environment and in analyzing issues and problems at ease. This course
exposes students to the basic knowledge on application of concepts in order to appreciate
mathematics and statistics as tools for business analysis. This course also enables the students to
appreciate data analysis methodologies and application of the concepts to understand the behavioural
analysis of the problems.
Pedagogy:
a) Clarification and conceptualisation through examples.
b) Application of the concepts through cases and assignments.
Evaluation Pattern:
Class Participation (Min. 75%
attendance)
10%
Assignments 10%
Viva 10%
Mid Term 20%
End Term 50%
Suggested Readings
Fundamentals of Statistics- S.C. Gupta, Himalaya Publishing House Pvt. Ltd
Business Statistics using Excel, 2/e, Glyn Davis & Branko Pecar, Oxford University Press.
Business Mathematics and statistics, 6e, Andre francis , Thomson Learning
Fundamentals of Mathematical statistics, S.C Gupta and VK kapoor , Sultan chand &Co
Detailed Description
The detailed description of the course is provided below as per the session wise distribution of the
course.
Session Plan
Session 1-2: Tables, charts, Graphical representation of data, frequency distributions
Session 3-6: Statistical Measures, Measures of central tendency, Measures of dispersion
Session 7-10: Functions and graphs, linear equations, quadratic and cubic equations, Cost, revenue and
profit functions.
Session11-15: Compounding, discounting and annuities, present value, investment appraisal, future
value
Session 16-19: Time series analysis, time series trend, season variation and forecasting
Session 20-23: Matrix theory, definitions, matrix orders, types, basic matrix operations, determinant,
inverse of a matrix
Session 24-25: Introduction to Probability, Basic ideas, Conditional probability, Probability tree
diagrams
Session 26-27: Probability Distributions Continuous distributions, discrete distributions
Session 28-29: Sampling Distributions and Estimating, Sampling, Point estimates, Confidence intervals
2. Session 30: Linear Correlation and Regression Analysis, Linear Correlation analysis, Linear
Regression analysis.
