Course Outline: Business Statistics
Course code: QM502
Credit:3 , Core Course
Area: Operations and Quantitative Method
Program: PGDM
Term II Academic Year 2022-23
_______________________________________________________________________
Prof. Shraddha Mishra
(Sec A & B)
003 (MDP Bldg.)
Prof. Arvind Seth
(Sec E)
Room no.
Prof. Deepak Chawla
(Sec C & D)
203
Email
dchawla@imi.edu
Shraddha.mishra@imi.edu
arvindseth99@gmail.com
Phone (Extn no.)
7838744410
9717261384
9205453637
Meeting Hours
Friday (2:30-4:30 pm)
Monday (2:00-4.00 pm)
Instructor(s) Name
______________________________________________________________________
1. COURSE DESCRIPTION
The course aims to enhance an understanding of quantitative information by building analytical skills. The
students will learn how to develop models, carry out data analysis, interpretation and make objective
decisions related to problems faced in business. The students will use EXCEL & SPSS software for analyzing
statistical data. The course also aims to prepare the students to use various quantitative tools which can
be applied for decision making.
2. COURSE OUTCOMES (COs)
After going through the course, the students would be able to:
COs >>
COs and POs >>
COs, POs and CECs >>
Course Outcome 1 (CO1): Formulate the decision problem by identifying various alternatives.
Course Outcome 2 (CO2): Identify the data analysis needs.
Course Outcome 3 (CO3): Analyze the data using appropriate technique to reach valid conclusions.
Course Outcome 4 (CO4): Apply the knowledge to interpret the findings and communicate the same
to management through written and oral presentation.
COs >>
COs and POs >>
COs, POs and CECs >>
3. MAPPING OF THE PROGRAM OUTCOMES (POs) AND COURSE OUTCOME (COs)
Course Outcomes (COs)
Program Outcomes (POs)
CO1
CO2
CO3
CO4
PO1: Student should be able to write well organized and grammatically
correct business reports and letters.
2
PO2: Student should be able to make effective oral presentations.
2
PO3: Student should be able to demonstrate critical thinking skills by
understanding the issues, evaluating alternatives on the basis of multiple
perspectives and presenting a solution including conclusions and
implications.
PO4: Student should be to demonstrate problem solving skills by
understanding and defining the problem, analyzing it and solving it by
applying appropriate theories, tools and techniques from various
functional areas of management.
2
3
3
3
3
3
PO5: Student should be able to illustrate the role of responsible
leadership in management.
PO6: Student should be able to identify social concerns and ethical
issues in management.
1
PO7: Student should be able to identify challenges faced by the
organization at the global level.
PO8: Student should be able to take decisions in the global business
environment.
4. PEDAGOGY
The course will be based on Class room lectures, Exercises based on class-discussions, cases, and groupproject. Students would have to work individually as well as in groups. Students are expected to read the
relevant chapters from the book and any other reading material provided before they come to the class.
5. COURSE EVALUATION COMPONENTS (CECs)
CEC1: Quizzes (2 out of 3)
CEC2: Mid-term Examination
CEC3: End-term Examination
CEC4 : Group Project/Case Presentation/Assignment
Total
20%
30%
40%
10%
100%
6. MAPPING BETWEEN COs, POs and CECs
Course Evaluation Components (CECs)
COs
POs
CO1
CO2
CO3
CO4
PO4
PO3, PO4
PO3, PO4, PO6
PO1, PO2, PO3
CEC1: Quiz
CEC2: Midterm
Examination
CEC3: Endterm
Examination
√
√
√
√
√
CEC4: Group
Project/Case
Presentation/Assignment
√
√
√
7. RESOURCES
7.1 Textbook
1. R I Levin, and David S Rubin (2017), “Statistics for management”, (Pearson Education India. Eight
edition).
7.2 Reference Books
1. Aczel Amir D and Sounderpandian J Complete Business Statistics, Tata McGraw Hill (7th edition,
2012).
2. David R Anderson, Dennis J Sweney and Thomas A Williams (2007), “Statistics for Business and
Economics”, Thompson South Western (Ninth edition).
3. Gerald Keller, “Statistics for Management”, 4th Indian edition (Thomson South-Western, a division
of Thomson Learning Inc., 2009), 718 pp.
4. Naval Bajpai, “Business Statistics”, (Pearson Education South Asia, 2013 edition), 794 pp.
5. Ken Black, “Business Statistics”, (Wiley India 5th edition), pp 839
6. D. Chawla & N. Sodhi “Research Methodology, Concepts and Cases”
7.3 Online References (if any)
Click or tap here to enter text.
8. SESSION PLAN
Session
No.
Topic
DECISION THEORY
1-2




Decision Environment
Expected profit under uncertainty
assigning probability values
Expected values of perfect information
Decision tree analysis
SAMPLING AND SAMPLING DISTRIBUTIONS
(NON-PROBABILITY & PROBABILITY SAMPLING)
3-5









Various sampling concepts
Random and Nonrandom Sampling
Sampling vs. census
Sampling error
Non-sampling error
Probability and non-probability sampling
methods
Sampling distribution of mean, Central
Limit Theorem
Sampling distribution of proportion
Sampling from a Finite Population
ESTIMATION



6-7



Point estimation
Interval estimation
Confidence interval for mean using Z
distribution
Confidence interval for mean using t
distribution
Confidence interval for proportion using Z
distribution
Determination of sample size while
estimating mean and proportion
Reading & Cases
Read: Pages 897 - 907, 925-934
Attempt: SC 17.1, 17.7, 17.8, 17.6, 17.8
Read: Pages 268 to 308 from Text
Attempt: Exercises 6.6, 6.8, 6.12, 6.17, SC 62. SC 6-3, 6.24, 6.25, 6.26, 6.28,
6.34, 6.35, 6.36, 6.37, 6.40, 6.41,
6.44, SC 6-8 from text
Read:
Pages 316 - 362 from Text
Attempt: Exercises SC 7-1, 7.12, 7.15, 7.17,
SC7-6, 7.25, 7.28, 7.34, 7.38, SC 710, 7.40, 7.42, 7.44, 7.45, 7.49 and
7.51 from text
Case : Presidential Polling
TESTING OF HYPOTHESES
8-9








Various concepts
One tailed test and two tailed test
Type 1 error and type II error
Level of significance
Power of test
Testing hypotheses concerning
population mean
Large sample test
Sampling sample test
TESTING OF HYPOTHESES CONCERNING
DIFFERENCES OF POPULATION

10-11


The case of population standard
deviation being known
The case of population standard
deviation being unknown
The case of paired sample
TESTING OF HYPOTHESES CONCERNING
PROPORTION AND DIFFERENCE BETWEEN
PROPORTIONS
12


Test of proportion (single population)
Test of proportion (two population)
Read:
Pages 371 - 390 and 397 – 403
from Text
Attempt: Exercises SC 8-3, 8.19, 8.20, SC 85, 8.28, 8.33, 8.45 and 8.48 from Text
Cases
 Cut Craft Cutlery
 Perception of people about ban on
plastic bags in Delhi
Read :
Pages 411 - 441 from Text
Attempt: Exercises 9.2, 9.3, 9.8, SC 9-6 and
9.13 from Text
Cases
 Compensation for Faculty Member
 Tiresome Tires II
 Comparative perception of Mess
Food vis a via Dhabas – A case of
IIFT
Read:
Pages 405 - 411 and 455 – 463
from Text
Attempt: Exercises 8.39, SC 8-10, 8.43, 9.18
and 9.20 from Text
Cases:
 Airline Satisfaction Survey
 Ice cream markets in India
 Tata tea
13-15
NON-PARAMETRIC STATISTICS
 Test for equality of more than two
population proportion
 Relationship between variables –
contingency table
 Test of population standard deviation
 Confidence internal for standard
deviation
 Goodness of fit of distribution
Read : Pages 732-736, 758-761
Attempt : 14.25, 14.27, 14.29, SC 11.1, SC
11.8, 11.38, 11.40, 11.42, 11.44, 11.45
Cases:
 Quality Associates, Inc.
 Indian Bicycle Industry
 Data Facts Research
TEST FOR EQUALITY OF TWO VARIANCE
16
Read : Pages 576-580
Attempt: 11.46, 11.50, 11.51
17
18-20
ANALYSIS OF VARIANCE (ONE WAY
CLASSIFICATION) INCLUDING POST-HOC
ANALYSIS
Read: Pages 542-547, SC 11.5, 1.25, 1.26
CORRELATION AND REGRESSION ANALYSIS
Read:








Pages 596 – 649 from Text
Attempt: Exercises 12.16, 12.31 and 12.37
Concept, Correlation coefficient
from Text
Rank order correlation coefficient,
Limitation of correlation theory
Simple linear regression model estimation Cases
 Exercise on Demand Function
Test of significance of regression
Estimation
coefficient
2
2

Mountain
States Potato Co.
r , significant of r
Multiple regression, test of significance
R2, Use of regression in point & interval
forecast (exact & approximate interval)
9. ACADEMIC INTEGRITY & CLASS RULES
a) Plagiarism is the use of or presentation of ideas, works that are not one’s own and which are not
common knowledge, without granting credit to the originator. Plagiarism is unacceptable in IMI
and will invite penalty. Type and extent of penalty will be at the discretion of the concerned faculty.
b) Cheating means using written, verbal or electronic sources of aid during an examination/ quiz/
assignment or providing such assistance to other students (except in cases where it is expressly
permitted by the faculty). It also includes providing false data or references/list of sources which
either do not exist or have not been used, having another individual write your paper or assignment
or purchasing a paper for one’s own submission. Cheating is strictly prohibited at IMI and will
invite penalty as per policies of the Institute.