BIG Corporation advertises that its light bulbs have a mean lifetime, μ, of 2800 hours. Suppose that we have reason to doubt this claim and decide to do a statistical test of the claim. We choose a random sample of light bulbs manufactured by BIG and find that the mean lifetime for this sample is 2620 hours and that the sample standard deviation of the lifetimes is 650 hours. In the context of this test, what is a Type II error?

A type II error is (rejecting/failing to reject) the hypothesis that μ is (less than/less than or equal to/greater than/greater than or equal to/not equal to/equal to) when in fact, μ is (less than/less than or equal to/greater than/greater than or equal to/not equal to/equal to) .

A type II error is failing to reject the hypothesis that μ is equal to 2800 when in fact, μ is less than 2800.

Step-by-step explanation:

A Type II error happens when a false null hypothesis is failed to be rejected.

The outcome (the sample) probability is still above the level of significance, so it is consider that the result can be due to chance (given that the null hypothesis is true) and there is no enough evidence to claim that the null hypothesis is false.

In this contest, a Type II error would be not rejecting the hypothesis that the mean lifetime of the light bulbs is 2800 hours, when in fact this is false: the mean lifetime is significantly lower than 2800 hours.

3x + 4y -25 =0 represents the amount of change sianna should recieve

step-by-step explanation: