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ASSIGNMENT
DRIVE
|
SUMMER 2014
|
PROGRAM
|
MBADS
/ MBAN2 / MBAHCSN3 / MBAFLEX – (SEM 3)
PGDENMN
/PGDFMN/ PGDHRMN / PGDHSMN / PGDIB /
PGDISMN
/ PGDMMN / PGDOMN / PGDPMN /PGDROMN / PGDSCMN / PGDTQMN – (SEM 1)
|
SUBJECT
CODE & NAME
|
MB0050
- RESEARCH METHODOLOGY
|
BK
ID
|
B1700
|
CREDITS
|
4
|
MARKS
|
60
|
Note:
Answer all questions. Kindly note that answers for 10 marks questions should be
approximately of 400 words. Each question is followed by evaluation scheme.
1
How would you distinguish between a management decision problem and a
management research problem? Do all decision problems require research? Explain
and illustrate with examples.
Answer : Decision Problem and Research Problem
Drivers
for problem formulation:
1.
Unaticipated change,
basically in the environment of the
focal firm
(suppliers,competitors, customers)
2.
Planned change (estimation,
effects, outcome)
3.
Serendipity (random ideas
or information)
Differetn
Problem Levels:
1)
Individual orientation,
PSYCHOLOGY
2
How are research designs classified? What are the distinguishing features of
each? Differentiate by giving appropriate examples.
Answer : The research design refers to
the overall strategy that you choose to integrate the different components of
the study in a coherent and logical way, thereby, ensuring you will effectively
address the research problem; it constitutes the blueprint for the collection,
measurement, and analysis of data.
Action
Research Design
3
Discuss with the help of examples the four key levels of measurement. What
mathematical operations/statistical techniques are and are not permissible on
data from each type of scale?
Answer : 4 Levels of Measurement
Nominal
Scale
The nominal scale (also called dummy
coding) simply places people, events, perceptions, etc. into categories based
on some common trait. Some data are naturally suited to the nominal scale such
as males vs. females, redheads vs. blondes vs. brunettes, and African American
vs. Asian. The nominal scale forms the basis for such analyses as Analysis
4
Processing of data involves editing, coding, classifying and tabulating.
Explain each of these steps by taking an appropriate example.
Answer : After collecting data, the
method of converting raw data into meaningful statement; includes data
processing, data analysis, and data interpretation and presentation.
Data reduction or processing mainly
involves various manipulations necessary for preparing the data for analysis.
The process (of manipulation) could be manual or electronic. It involves
editing, categorizing the open-ended questions, coding, computerization and
preparation of tables and diagrams.
5
Distinguish between the following:
a.
Null hypothesis and Alternative hypothesis
Answer : The Null Hypothesis
The null hypothesis reflects that
there will be no observed effect for our experiment. In a mathematical
formulation of the null hypothesis there will typically be an equal sign. This
hypothesis is denoted by H0.
b.
One tailed and two tailed tests
Answer : A one- or two-tailed t-test
is determined by whether the total area of a is placed in one tail or divided
equally between the two tails. The one-tailed t-test is performed if the
results are interesting only if they turn out in a particular direction. The
two-tailed t-test is performed if the results would be interesting in either
direction. The choice of a one- or two-tailed t-test effects the hypothesis
testing procedure in a number of different ways.
c.
Type I and Type II error
Answer : Type I error
A type I error occurs when one rejects
the null hypothesis when it is true. The probability of a type I error is the
level of significance of the test of hypothesis, and is denoted by *alpha*.
Usually a one-tailed test of hypothesis is is used when one talks
d.
One way and two way analysis of variance
Answer : The two-way analysis of
variance is an extension to the one-way analysis of variance. There are two
independent variables (hence the name two-way).
Assumptions
·
The populations from which the samples were
obtained must be normally or approximately normally distributed.
·
The samples must be independent.
·
The variances of the populations must be
equal.
e.
Descriptive and inferential analysis of data
Answer : Descriptive Statistics :
Descriptive
statistics includes statistical procedures that we use to describe the
population we are studying. The data could be collected from either a sample or
a population, but the results help us organize and describe data. Descriptive
statistics can only be used to describe the group that is being studying. That
is, the results cannot be generalized to any larger group.
6
a. What is Chi-square test of goodness of fit? What precautions are necessary
while applying this test? Point out its role in business decision making.
Answer :
Chi-square is a statistical test
commonly used to compare observed data with data we would expect to obtain
according to a specific hypothesis. For example, if, according to Mendel's
laws, you expected 10 of 20 offspring from a cross to be male and the actual
observed number was 8 males, then you might want to know about the
"goodness to fit" between the observed and expected. Were the
deviations (differences between observed
b.
Two research workers classified some people in income groups on the basis of
sampling studies. Their results are as follow:
Investigators
|
Income groups
|
Total
|
||
Poor
|
Middle
|
Rich
|
||
A
|
160
|
30
|
10
|
200
|
B
|
140
|
120
|
40
|
300
|
C
|
300
|
150
|
50
|
500
|
Show
that the sampling technique of atleast one research worker is defective.
Answer : Let us take the
hypothesis that the sampling techniques adopted by research workers are
similar(i.e. there is no difference between
the techniques adopted by research workers).This being so, the
expectations of A investigator classifying the people in
(I)Poor Income Group : =200 x 300 /500 =120
Dear
students get fully solved assignments
Send
your semester & Specialization name to our mail id :
“ help.mbaassignments@gmail.com ”
or
Call
us at : 08263069601
(Prefer
mailing. Call in emergency )
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