Course

Unit 1

Data representations and analysis

Meaning and scope of statistics, collection of data, primary and secondary methods of data collection, classification of data, presentation of data by diagrams, bar diagram and pie diagram.

Unit 2

Arithmetic mean, median, mode, properties and uses, measures of dispersion – quartile deviation, standard deviation and co-efficient of variation.

Unit 3

Probability

Introduction, Classical definition of probability, Addition theorem, Multiplication theorem, independence of events, conditional probability.

Unit 4

Correlation, regression and time series Analysis

Correlation – meaning and definition, scatter diagram, Karl Pearson’s correlation coefficient,

computation and interpretation; Regression, the two regression equations.

Time series – meaning and components, business forecasting, methods of estimating trend, graphic, and semi average, moving average method.

Unit 5

Operations Research

Linear programming problem, introduction, mathematical formulation of the problem, graphical solution, standard form of LPP, solution of LPP by simplex method. Network Scheduling by CPM, introduction, Activities and events, network diagram.

Course Objective:

To develop an understanding of problem-solving methods, to understand the basic concepts of statistics and operations research, and to apply the results to real-life business problems.

Course Outcomes:

The student will be able to:

CO1: Introduce various methods of collection, classification, tabulation, and representation of data.

CO2: Explains and evaluates the measures of central tendency and measures of dispersion.

CO3: Understand the random experiment, sample space, and evaluation of the probability using the classical definition of probability and its application in real-life situations.

CO4: Analyze the data using methods of correlation and regression. Also describes mathematical considerations for analyzing time series and methods of Estimating trends.

CO5: Identify and develop operational research models from verbal descriptions of the real system and understand the mathematical tools that are needed to solve optimization problems.

Text Books:

1. P. Gupta – Statistical methods – Sultan Chand and Sons.
2. Kantiswaroop K Gupta, Manmohan – Operations Research – Sultan Chand and sons

References:

1. R. Vittal – Business mathematics and statistics – Margham Publications
2. R Potti – Operations Research – Yamuna Publications.