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Two Sample Tests
In some situation the researchers may be taking statistical decisions based on two samples. Each of the two samples may represent a particular under consideration. For example one may be interested to study the effectiveness of teaching methods like unstructured teaching and structured teaching. Suppose college have changed their method of teaching from unstructured teaching to structured teaching recently. Then the researcher has to take a random sample of students of a particular programme from different colleges and collect their performances before introducing the structured methods of teaching and after introducing the structured method of teaching. The respective observation will form two samples .
There are many more examples which are as listed below:
a.Number of defects found in the daily lots of items produced by a set of similar machines before and after installing a costly automatic inspection systems in them.
b. Monthly sales revenues of a product in different regions before launching an advertisement campaign and after launching the advertisement campaign.
c.Number of daily transaction in a bank before and after introducing computers.
d. Number of outpatients treated in a government hospital before and after providing modern infrastructure.
There are various non parametric tests but we will discuss only a few of the better known and more widely used ones.
a.The sign test
1. One samples test
2.Two sample sign test ( sing test for paired data)
3.A rank sum test ( Mann Whitney u test)
4. The one sample runs test
5.Rank correlation ( described in chapter 10 )
Consider a queueing system with 1 counter, to which groups of customers arrive according to a Poisson proces with intensity l. The size of a group is 1 with probability p and 2 wit
source code in c available?
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Solve the following Linear Programming Problem using Simple method. Maximize Z= 3x1 + 2X2 Subject to the constraints: X1+ X2 = 4 X1 - X2 = 2 X1, X2 = 0
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Ask question #Minimum 100 woRead this article and then write a three-page summary of the application (problem definition, objective function constraints, decision variables, etc.)
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