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School of Management and Entrepreneurship (SNU)

MBA

ACADEMIC YEAR 2014-2015

TERM-1

Name of the Instructor: Surya Sarathi Majumdar

Telephone Ext. No./Mobile Phone No. /0091 9831918230

E-mail ID: surya.majumdar@snu.edu.in

Office Location: C214-B

Subject Title Quantitative Techniques in Management - I

Subject Code

Credit Value 2

Levels Post-Graduate

Total Teaching Contact

Hours

30

Prerequisites None

Objective 1)

Teach how to calculate the probability of certain outcomes based

on prior data.

2)

Impart knowledge on how to present and manipulate statistical

data and draw inferences from same.

3)

Teach methods to test statistical data for existing patterns.

4)

To use inferences drawn from data to predict future results and

forecast trends.

Subject Learning Outcomes a)

Learn about permutations, combinations, and Bayes theorem

(Objective 1)

b)

Learn how to present data using various charts and graphs

(Objective 2)

c)

Learn about ways of measuring statistical data such as mean,

median, mode, deviation and variance, and probability

distributions (objective 2)

d)

Learn about how to take samples, form estimates, and test for

hypotheses regarding the data (objectives 2 and 3)

e)

Analyzing the variance in existing data (objectives 2 and 3)

f)

How to predict outcomes by drawing simple or multipleregression lines on existing data (objectives 3 and 4)

g)

Learn how to analyze and forecast trends and variations in data

over time (objective 4)

h)

Learn how to perform all the above functions using a computer

and large examples (objectives 1 to 4)

Subject Synopsis/ Indicative

Syllabus

Simple probability calculations, Permuations and Combinations, Bayes

Theorem; Presentation of data using charts and graphs; mean, median

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and mode, variance and standard deviation; random variables and

probability distributions; Sampling Methods; Estimation, point and

interval; Hypothesis Testing, using parametric and non-parametric data;

ANOVA; Correlation and regressionsimple, multiple, polynomial;

forecasting and trend analysis

Session plans See following page (with following details for each session)Topics

Reading

Case/Exercise

Teaching/ Learning

Methodologies

Classroom lectures and practice exercises

Assessment Specific assessment methods/tasks weighta

Quizzes Best 6 out of 8 60%

Mid-term 20%

End-term 20%

Total 100%

Reading Lists and reference

books/ materials etc

Statistics for Management 7th

Ed., by Levin, Rubin, Rastogi, & Siddiqui

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School of Management and Entrepreneurship (SNU)

Session Topics covered Reading Exercises

1. Introduction to Probability,

Permutations and combinations,

Conditional probability, Bayesian

equation

SfM Ch.4

2. Introduction to statistics, and organizingstatistical datafrequency distributions,

charts, graphs

SfM Ch.2

3. Simple statistical measuresmean,

median, mode, quartiles,

SfM Ch. 3.1 Quiz 1Syllabus Sessions 1-2

4. Statistical measuresvariance and

standard deviation, shape and skew of

data,

SfM Ch. 3.2-3.6

except 3.5

5. Random variables, probability density

and distribution, expected values

SfM Ch. 5.1-5.2 Quiz 2Syllabus Sessions 3-4

6. Probability distributionsbinomial,

poisson, normal

SfM Ch. 5.3-5.5,

Ch.6

7. Introduction to sampling, experiment

design

Quiz 3Syllabus Sessions 5-6

8. Sample distributions, , random sampling

with/without replacement, central limit

theorem

SfM Ch.7

9. EstimationPoints and Interval

Estimates

SfM Ch.8 Quiz 4Syllabus Sessions 7-8

10. Mid-term review

11. Hypothesis testing, Errors in testing,

Creating a hypothesis, testing methods

SfM Ch.9

12. Two sampling testing, test for difference

between means, between proportions

SfM Ch. 10

13. Testing for nonparametric data, signed

tests, rank-sum tests, rank correlation,

mcnemar test

SfM Ch. 12.4-12.6 Quiz 5Syllabus Sessions 11-

12

14. Chi-square test and Analysis of Variance SfM Ch.11, 12.1-

12.3, 12.7

15. Introduction to correlation and

regression, covariance and correlation

coefficient, simple linear regression

SfM Ch.13 Quiz 6Syllabus Sessions 13-

14

16. Multiple linear regression SfM Ch. 14

17. Model-building on multiple regression,

Polynomial regression

SfM Ch.15 Quiz 7Syllabus Sessions 15-

1618. ForecastingTime Series and Trend

Analysis

SfM Ch.16.1-16.5

19. Time series variationsCyclical,

Seasonal, Irregular

SfM Ch.16.6-16.8 Quiz 8Syllabus Sessions 17-

18

20. Finals review