CODE 1430 ASSIGNMENT 2
Q 1 a : Explain the terms : point Estimate and interval Estimate,Type-1 Error and type II Error, estimate and estimator, test statistic, power of test ? B A random sample of 20 students was taken in two sections A&B of statistics and probability class. The example from segment A had a normal characteristic of 8 and a standard deviation of 2 in midterm exam.the test from segment B had a normal sign of 12 and a standard deviation of 4 in midterm exam Test whether there is significant difference between the mean marks of section A &.USE A 5% LEVEL OF SIGNIFICANCE. Answer a : Point Estimate and Interval Estimate A gauge of a populace parameter might be communicated in two ways :
POINT ESTIMATION : A point gauge of a populace parameter is a solitary estimation of a measurement. Example : the sample mean X is a point estimate of the population mean u. So also, the specimen extent p is a point gauge of the populace extent p. Interim ESTIMATION : An interim gauge is characterized by two numbers, between which a population parameter is said to lie. For Example a < x < b is associate degree interval estimate of the population mean u.it indicates that the population mean is larger than a little but b. In any estimation issue, we have to get both a point gauge and an interim gauge. The point gauge is our best figure of the genuine estimation of the parameter, while the interval estimate gives a measure of accuracy of that point estimate by providing an interval that contains possible values. Type-I and Type-II Error When you do a hypothesis test, two types of errors are possible : type I and type II. The dangers of these two blunders are contrarily related and controlled by the level of importance and the power for the test. Therefore, you should determined which error has more severe consequences for your situation before you define there risks. No hypothesis test is 100% certain. Since the test depends on probabilities, there is dependably a shot of making a wrong determination.