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ASSIGNMENT
Course Code : MS - 95
Course Title : Research Methodology for Management Decisions
Assignment Code : MS-
95/TMA/SEM-I/2014
Coverage : All Blocks
Note : Attempt all the
questions and submit this assignment on or before 30th April , 2014 to the
coordinator of your study centre.
1.
Make a comparison of Completely
Randomized Design (CRD), Randomized complete Block Design (RBD) and Latin
Square Design (LSD) in terms of role, the model and the assumptions embodied in
the model.
Ans
: Completely Randomized Design (CRD) :
In the design of
experiments, completely randomized designs are for studying the effects of one
primary factor without the need to take other nuisance variables into account.
This article describes completely randomized designs that have one primary
factor. The experiment compares the values of a response variable based on the
different levels of that primary factor. For completely randomized designs, the
levels of the primary factor are randomly assigned to the experimental units.
Randomization:
By
randomization, that is to say the run sequence of the
2.
You are given a sample of 100 people and are asked to do an image study of
three neighbourhood multiplexes. Assume any average ratings based on people's
attitude and construct a Semantic Differential Scale by defining appropriate
adjectives.
Ans
: Semantic Differential Scale :
Semantic
differential is a type of a rating scale designed to measure the connotative
meaning of objects, events, and concepts. The connotations are used to derive
the attitude towards the given object, event or concept.
Osgood's
semantic differential was an application of his more general attempt to measure
the semantics or meaning of words, particularly adjectives, and their referent
concepts. The respondent is asked to choose where his or her position lies, on
a scale between two bipolar adjectives (for example:
"Adequate-Inadequate", "Good-Evil" or
"Valuable-Worthless"). Semantic differentials can be used to measure
opinions, attitudes and values on a
3.
What is multiple regression? In what ways can multiple regression be used to
forecast some industry’s sales?
Ans
: Multiple regression:
The general
purpose of multiple regression (the term was first used by Pearson, 1908) is to
learn more about the relationship between several independent or predictor
variables and a dependent or criterion variable. For example, a real estate
agent might record for each listing the size of the house (in square feet), the
number of bedrooms, the average income in the respective neighborhood according
to census data, and a subjective rating of
4.
Describe, in brief, the importance of editing, coding, classification,
tabulation & presentation of data in the context of research study.
Ans
: Importance of editing, coding,
classification, tabulation & presentation of data in the context of
research study:
Data required
for the purpose of analysis & presentation of a research study is often
consisting of errors such errors must be rectified before the final
presentation is made.
This process
involves editing, coding, classification, tabulation & presentation of
data.
Editing-
This is
concerned with removal of redundant data, filling of missing data completeness
of data substance & reliability of data. The data obtained from variance
sources are not always complete-sometimes fields remain black due to the human
5.
The values below are the scores (maximum 20) obtained in an aptitude test by a
random sample of 11 graduates. It is
known that for the non-graduate population the median score is 12. Is there
evidence, at the 10% significance level, that graduates achieve a higher median
score than the non-graduate population?
|
14
|
15
|
9
|
10
|
10
|
13
|
14
|
19
|
12
|
16
|
13
|
Ans
:
H0 :
Ƞ = 12
H1 :
Ƞ > 12 (One tailed )
Significance
level α = 0.10
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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