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##### Sanjukta Mohanty Category

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# Code(Credit) : CUBC2431 (2+2+0)

## Course Objectives

The objective of this course is to familiarize students with the basic statistical tools used for managerial decision-making.

## Learning Outcomes

After successful completion of the course, the student will be able to:
• Produce appropriate graphical and numerical descriptive statistics for different types of data.
• Use simple/multiple regression models to analyze the underlying relationships between the variables through hypothesis testing.
• Conduct and interpret a variety of hypothesis tests to aid decision making in a business context.

## Course Syllabus

Unit-1:
Statistics: Definition, scope and its limitations. Introduction to sampling, Random sampling vs. non-random sampling, Types of sampling, Simple random sampling, stratified random sampling, systematic cluster sampling, Distributions, standard error, sampling from normal production. Classification and tabulation of data.
Unit-2:
Measures of Central Value: Introduction, Definition and Objectives, Requisites of a Good Average. Types of Averages: Arithmetic Mean, Median, Mode, Geometric Mean and Harmonic Mean, advantages and limitation. Which average to use?
Unit-3:
Measures of Dispersion: Introduction, Dispersion Defined, Properties of Good Measure of Variation. Methods of Studying Variation: Absolute and Relative Measure of Variation, Range, The Interquartile Range, The Quartile Deviation, The Mean Deviation, The Standard Deviation, Lorenz Curve, Which Measure of Dispersion to Use?
Unit-4:
Regression and Correlation analysis: Introduction: Significance of the Study of Correlation, Types of Correlation, Methods of Studying Correlation. Use of Regression Analysis: Difference between Correlation and Regression Analysis, Regression Lines, Regression Equations.
Unit-5:
Testing hypothesis- Introduction, procedure of testing hypothesis, concept type I and II errors. Two tailed and one-tailed Tests of Hypothesis. Introduction to chi-square tests and goodness of fit, uses of chi-square tests.

Books recommended:

1. Chandrajit S. Statistics For Business & Economics. Vikas
2. Statistics for Management - Levin and Rubbin, Prentice Hall Of India.
3. Fundamentals of Statistics ( Vol-I & Vol-II) Goon, Gupta, Dasgupta, World Press Pvt. Ltd.
4. A First Course In Statistics With Applications - A.K. P.C. Swain, Kalyani Publishers.
5. Quantitative methods, Millhad Saha & Chakrabarti, TMH
6. Statistical Methods- S. P. Gupta

## Session 2

Classification and tabulation of data, standard error, sampling and types of sampling.

Sampling error & Non Sampling error

Classification of data

## Session 3

Introduction to sampling, Random sampling vs. non-random sampling, Types of sampling, Simple random sampling, stratified random sampling, systematic cluster sampling,

samplingtechniques

sampling-stratified vs cluster

sampling-introduction

## Session 4

Measures of Central Value: Introduction, Definition and Objectives, Requisites of a Good Average.

## Session 5

Types of Averages: Arithmetic Mean, Methods of Calculating Arithmetic Mean,

https://www.youtube.com/watch?v=I33mWfH8Noc (Arithmetic mean for  Grouped data)

## Session 6

Missing Frequency in Arithmetic Mean

## Session 7

Practice class on Arithmetic Mean.

Problem Practice on different methods of Arithmetic Mean.

Problem Practice on missing Frequency.

## Session 8

Properties of Arithmetic Mean.

## Session 10

Practice Session on Median

Problem Practice on median on different methods for discrete and continuous series.

## Session 12

Practice Class on Mode

Problem Practice

## Session 13

Calculation of Geometric Mean .

Properties of Geometric mean

B.Com Sem I STBM Log-Antilog-Tables

Properties of GM

## Session 14

Calculation of Harmonic Mean

## Session 15

Practice Session on Geometric Mean and Harmonic Mean

Problem Practice.

## Session 16

Introduction, Dispersion Defined, Properties of Good Measure of Variation.

## Session 17

Methods of Studying Variation: Absolute and Relative Measure of Variation, Range

## Session 18

The Interquartile Range, The Quartile Deviation- Merits and Demerits

## Session 19

The Mean Deviation, Different methods to measure Mean Deviation- Advantages and dis advantages

## Session 20

The Standard Deviation. Different Method- Merits and demerits

## Session 21

Practice Session on measures of dispersion.

Problem Practice.

## Session 22

Graphical method of measures of Dispersion

Lorenz Curve

## Session 23

Introduction on Correlation: Meaning and types of correlation.

## Session 24

Types of Correlation, Methods of Studying Correlation.

## Session 25

Use of Regression Analysis: Difference between Correlation and Regression Analysis, Regression Lines, Regression Equations

https://www.youtube.com/watch?v=qA-x72ju2kM (difference between correlation and regression)

## Session 26

Testing hypothesis- Introduction, procedure of testing hypothesis

hypothesistesting

Z test & Standard Error

## Session 27 & 28

concept type I and II errors. Two tailed and one-tailed Tests of Hypothesis.

testingofhypothesis

## Session 29 & 30

Introduction to chi-square tests and goodness of fit, uses of chi-square tests.

chi-squaredtest

chisquaretest

## Session 31 & 32

Revision Classes, Problem Practice, Doubt Clearing

## Case Studies 