What is the difference between objective and subjective probability
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Quantitative Methods
Case Studies
Multi Criteria Decision Making (20
Marks)
MCDA. (Multi criteria decision
analysis) is considered to be one of the fastest growing research operations in
the last several years. The researcher focus towards MCDA led to development of
many different approaches and ways in the field. There are two types of
procedures: theoretical assumptions and decision addressed type. This
difference throws challenges to the procedure of choosing the most ideal method
for the decision making problem. Most of the time, the initial approach towards
applying MCDA in the real world problems relates to the set up of simple
understanding Of the context and recognizing the problem of decision. This step
includes the ones• who make decisions and other important participants who make
important contributions for the MCDA procedure by sharing their knowledge. The
common insight of the decision framework is received by knowing the goals of
the decision making body and recognizing not only those people who make
decisions but also those who face the decision. • Dooley (2009) says that the
first three steps take up more time in the process of MCDA, particularly
because of their qualitative features. Assigning of comparative significant
weights to the selected criteria is the next step: These weights can be
ascertained directly, for example ranking, swing, trade off; or indirectly, for
examplecentrality, regression and interactive. Later, the DM has to give
individual scores, considering his or her views, to each of the recognized
options according to the criteria which seem vital. These scores show the
decision of DM . related to spreading of each substitute to every performance
standard. The information which is attained is maintained distinctively into
performance template, which is also as consequence matrix, options matrix, or
just decision table. The next process includes abstract of the information
consisting of the performance matrix in the form of multi criteria scores, for
every possible plan. Mostly, this is attained by combining the individual
scores of matrix so that total valuation of .each substitute which allows more
comparison. The groups of substitute ranked on the basis of all these scores.
Finally, the procedure can include a warm evaluation of the outcome to
amendments in the scores or criteria, to conclude the sturdiness of the result
of MCDA. At the end, the analysis and trade offs included in the respective
choices are given to and conferred with the DM. In many cases, the ultimate
decision that DM takes, does not match with the highest level of alternative,
as they are more focused towards the process of knowing the effect of each and
every factor in ranking of choices than in the exactness of the ranking. Also,
it should be observed that the generalizations are not used to of the outcome
given by the process of MCDA, and they only appropriate for the group of
choices which were assessed.
Answer the following question.
Q1. What role does MCDA play in
decision making? (Hint: MCDA is considered to be one of the fastest growing
research operations, these scores show the decision of DM related to spreading
of each substitute to every performance standard)
Q2. What does MCDA stand for? (Hint:
multi criteria decision analysis)
Linear Programming (20 Marks)
Lexicographic Goal Programming is used
to solve a series of Linear Programming Model. This programming is used
when. a goal has to be attained on
•priority basis. Revenue budgeting is being used to decide budget instead of a
specific system in budget. Nevertheless, revenue budget lays emphasis on the
rising limitation of revenue while estimating budget. The decision makers
limited due to the rising power of capital and also the awareness of imminent
restraints and fear of capital resources. The goal is to raise the salary and allowance
of the workers, to cut down the operating cost, to raise the revenue expenses,
to raise the capital generated internally, and the cut down the overall budget.
Some of the problems are: insufficient allocation of funds and income, and•
absence of importance of order. The insufficient allotment occurred as the
quantitative allotment models were not used with power. . It is seen that the
allotment of capital were not being used in the right" way as a result the
capital allotted to the labs is drawn •in the maintenance of hostel. Various
other changes also happen. In fact, the funds allotted to the tertiary
organizations are more often not managed properly. The University of Owerri
suffered and the progress of the institution came down. There is absence of
active teams for monitoring budget, and so the budget can function in any
manner. If the active teams to monitor budget were present, the problem of
mismanagement and the wrong use of it would come down. Sundaram (1978) and Lee
(1972) agreed that the various features of target programming are, that it
allows ordinal solution. According to Igniio (1978), this tactic called Goal
Programming, frequently symbolizes considerable progress in the modeling and
evaluation of the multi objective problems. This shows that this area lets the
systematic evaluation of a number of multi objective problems which could
include linear or non linear operations in the incessant or separate variables.
This is most successful in the research area. The goal programming developed
due to Charnes and Cooper, who suggested that the model and method for dealing
with some linear programming problems where the contradictory 'goals of
management' involved as limitations. Goal programming method has been used for
a number of programs. Goal programming technique has solved the following
problems: planning production in a ship repairing company, smoothing production
in 'just in time' production atmosphere. The problem occurs when the model does
not show the real inclination of the decision maker. Noninferior solution in
some cases many not be essentially better than the lesser solution mainly in
the case of natural resource problem.
Answer the following question.
Q1. What are the problems while
estimating the budget? (Hint: insufficient allocation of funds and income, and
absence of importance of order, The insufficient allotment occurred as the
quantitative allotment models were not used with power)
Finoplastika Industries Ltd, Nigeria
(20 Marks)
Time series analysis has two important
aims: 1) recognizing the quality of the phenomenon shown by the series of
studies, and 2) Both the aims need the plan of the viewed time series data is
recognized and somewhat officially explained: A time series is said to be a
'collection of observations made in sequence with time'. For example: recording
level of daily rainfall, periodical total domestic product of US, and monthly
strength of the. workers in Marine Corps for a specific rank and MOS. The
evaluation of time series gives instruments for picking a symbolic model and
delivering forecasts. There are two sorts of times series data: • Continuous:
in this the data consists of study at every moment, for example, seismic
movement recorded on a seismogram. • Discrete: the data contains recordings
taken at different periods ,like, statistics of each month crime. Until the
data is absolutely haphazard, studies in time series are usually related to
each and the following studies could be partly ascertain by the last values.
For instance, the reasons pertaining to the meteorology which have an effect on
the temperature for any given day tend to have some affect on the next day's
climate. Hence, the observations of the past temperature are helpful for
predicting temperatures for the following days. • A time series can be
deterministic if there are no haphazard or feasible features but goes in a set
and foreseeable manner. The data gathered during the classical physics
experiment like showing Newton's Law of Motion, is one example of a
deterministic time series. The stochastic type of series is more appropriate to
the econometric function. Stochastic variables contain undefined or arbitrary
viewpoint. Though the worth of each study cannot be precisely foreseen,
calculating the various observations could follow the expected method. These
methods can be explained through the statistical models. According to these
models, studies differ erratically on the underlying mean value which is the
role of time. Time series data can be put in the following categories: one or
more performance factors; Trend, seasonality, cyclical function and random
sound. Various kinds of time series predicting models
give forecasts through extrapolating
the previous performance of the values of a specified \'l!riable of interest.
Consecutive study in econometric times
series are generally not free and forecast can be made on the basis of last
observations. Although precise predictions can be made with deterministic time
series, predictions of stochastic time series are restricted to 'conditional
statements regarding the future on the basis of particular hypothesis.'
Armstrong (2001) says, "The basic Assumption is that the variable ui!!
Continue in the future as it has behaved in the past. “Particularly, the time
series predictions are suitable for stochastic type of data in which the
fundamental root cause of variation like, trend, cyclical performance,
seasonality, and uneven variations, do not change radically m time. Therefore,
modeling is considered to be more suitable temporarily instead of permanent
predictions.
Answer the following question.
Q1. Write briefly on time series
analysis. (Hint: recognizing the quality of the phenomenon shown by the series
of studies, and, both the aims need the plan of the viewed time series data is
recognized and somewhat officially explained)
CASE STUDY (20 Marks)
The bulbs manufactured by a company
gave a mean life of 3000 hours with standard deviation of 400 hours. If a bulb
is selected at random, what is the probability it will have a mean life less
than 2000 hours?
Answer the following question.
Q1. Calculate the probability.
Q2. In what situation does one need
probability theory?
Q3. Define the concept of sample space,
sample points and events in context of probability theory.
Q4. What is the difference between
objective and subjective probability?
Assignment Solutions, Case study Answer sheets
Project Report and Thesis contact
ARAVIND – 09901366442 – 09902787224
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