Already have an account? Get multiple benefits of using own account!
Login in your account..!
Remember me
Don't have an account? Create your account in less than a minutes,
Forgot password? how can I recover my password now!
Enter right registered email to receive password!
TYPE I AND II Errors
If a statistical hypothesis is tested, we may get the following four possible cases:
The null hypothesis is true and it is accepted;
The null hypothesis is false and it is rejected;
The null hypothesis is true, but it is rejected;
The null hypothesis is false, but it is accepted.
Clearly, the last two cases lead to errors which are called errors of sampling. The error made in (c) is called Type I Error. The error committed in (d) is called Type II Error. In either case a wrong decision is taken.
P(Committing a Type I Error)
= P (The Null Hypothesis is true but is rejected)\ = P (The Null Hypothesis is true but sample statistic falls in the rejection region) = α, the level of significance
= P (The Null Hypothesis is true but is rejected)\
= P (The Null Hypothesis is true but sample statistic falls in the rejection region)
= α, the level of significance
P(Committing a Type II Error)
= P (The Null Hypothesis is false but sample statistic falls in the acceptance region) = β (say)
= P (The Null Hypothesis is false but sample statistic falls in the acceptance region)
= β (say)
The level of significance, α , is known. This was fixed before testing started. β is known only if the true value of the parameter is known. Of course, if it is known, there was no point in testing for the parameter.
Factor analysis (FA) explains variability among observed random variables in terms of fewer unobserved random variables called factors. The observed variables are expressed in
Two students are sitting in a lecture and considering whether to ask a question from the professor (both of them are considering the same question). If they both ask, the questi
Let X, Y, and Z refer to the three random variables. It is known that Var(X) = 4, Var(Y) = 9, and Var(Z) = 16. It is further known that E(X) = 1, E(Y) = 2, and E(Z) = 4. Furthermor
For a distribution of scores with = 82 and standard deviation = 2.5, find the following: (Don't forget to sketch the normal curve to help you visualize what you are trying to fi
Examples of grouped, simple and frequency distribution data
Admixture in human populations The inter-breeding amongst the two or more populations which were previously isolated from each other for the geographical or the cultural reason
In simple regression the dependent variable Y was assumed to be linearly related to a single variable X. In real life, however, we often find that a dependent variable may depend o
Suppose that in the actual survey of 50 prospective customers, 6 subscribe to the 3 for all offer, what does this tell you about the previous estimate of the proportion of customer
If the test is two-tailed, H1: μ ≠ μ 0 then the test is called two-tailed test and in such a case the critical region lies in both the right and left tails of the sampling distr
For each of the following situations choose the statistical model that you find to be the most appropriate. Justify your choice. a) We are interested in assessing the effects of
Get guaranteed satisfaction & time on delivery in every assignment order you paid with us! We ensure premium quality solution document along with free turntin report!
whatsapp: +91-977-207-8620
Phone: +91-977-207-8620
Email: [email protected]
All rights reserved! Copyrights ©2019-2020 ExpertsMind IT Educational Pvt Ltd