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The graphic representation of the alternatives in a decision making problem which summarizes all the possibilities foreseen by the decision maker. For instance, suppose we are given the below written problem.
A physician should choose between two treatments. The patient is known to have one of the two diseases but the diagnosis is not very certain. A thorough examination of the patient was not able to resolve the diagnostic uncertainty. The best which can be said is that the probability which the patient has disease A is p. An easy decision tree for the problem is shown in the figure drawn below.
Pie chart is an extensively used graphical technique for presenting relative frequencies related with the observed values of the categorical variable. The chart comprises of a cir
Personal probabilities : A radically special approach for allocating probabilities to events than, for instance, the commonly used long-term relative frequency approach. In this ty
CONSTRUCTION OF AN OR MODEL
Latent class analysis is a technique of assessing whether the set of observations including q categorical variables, in specific, binary variables, consists of the number of diffe
re-reference all these indexes
Non linear model : A model which is non-linear in the parameters, for instance are Some such type of models can be converted into the linear models by linearization (the s
Can I use ICC for this kind of data? Wind Month Day Temp(DV) 7.4 5 1 67 8 5 2 72 12.6 5 3 74 11.5 5 4 62 I am taking temp as the dependent variable. There are many more values.
The scatter plots of SRES1, RESI1 versus totexp demonstrates that there is non-linear relationship that exists as most of the points are below and above zero. The scatter plots sho
Ask questioThe finance manager of ‘Softy’ baby soap manufacturing company being successful in the first two years of the company’s operations is considering setting up another plan
Invariant transformations to combine marginal probability functions to form multivariate distributions motivated by the need to enlarge the class of multivariate distributions beyo
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