At a large company, employees can take a course to become certified to perform certain tasks. There is an exam at the end of the course that needs to be passed for certification. The current pass rate is 0.7, but a new program is being tested to help increase the pass rate. The null hypothesis of the test is that the pass rate for the new program is 0.7. The alternative is that the pass rate for the new program is greater than 0.7. What is the Type Il error and the consequence that could result from the test?

A large company of employees has to pass the test to get the certificate but the rate of passing is 0.7 after conducting the test of null hypothesis the type II error is occured in which predict the answer pass rate of new program is 0.7 to 0.8 to get the passing certificate.

Explanation to the above question

Type II error - A type II error, also known as an error of the second kind or a beta error, confirms an idea that should have been rejected, such as, for instance, claiming that two observances are the same, despite them being different.

A type II error does not reject the null hypothesis, even though the alternative hypothesis is the true state of nature. In other words, a false finding is accepted as true.

Thus we Conclude that from the test of the new program the passing rate 0.7 but after coming of the type II error its value is coming false negative which truly accepted 0.8 passing rate of the new employees to get the certificate.

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