______ hypothesis testing situations start with stating the _________ hypothesis.

A _________ hypothesis is a conjecture about the population parameter.

A statistical hypothesis is a conjecture about the ____________.

This ____________ may or may not be true

There are two types of statistical hypotheses: the _______ hypothesis and ________ hypothesis.

_________ Hypotheses, symbolized by _____ is a statistical hypothesis testing that assumes that the observation is due to a chance factor.

In hypothesis testing, _______ hypothesis is denoted by; H0:𝜇1 = 𝜇2, which shows that there is ____ difference between the two ____________ means (or parameters).

________ hypothesis, symbolized by ____, is the opposite of the null hypothesis.

It shows that observations are the result of a real effect.

It states that there is a difference between two population means (or parameters).

When dealing with hypothesis tests, there are ______ possible outcomes.

Based from the given table, a researcher commits an error if a ______ H0 is rejected or accepted by a ______ H0. When a researcher rejects a true H0, he commits a ________ error or ______ error. When a researcher accepts a false H0, he commits a _______ error or ______ error

A Type I error is committed when the researcher _______ a ______ hypothesis when in fact it is _____

A Type II error is committed when the researcher _______ a _______ hypothesis when in fact it is ________.

When a researcher tests the hypothesis, he is _____ certain that the decision is _____ correct. However, he is confident at a certain level that the decision is correct, say ____of the decision he made is a ________ one.

The confidence level is 99% or the level of significance is ____ When the confidence level is 95%, the level of significance is ____. On the other hand, when the confidence level is 90%, the level of significance is ____ In this case, the higher the confidence level, the _____ certain that the decision of _________ the _____ hypothesis is ________

In hypothesis testing, the ______________ refers to the degree of significance in which we accept or reject the ______ hypothesis.

It is the probability of committing a Type I error or alpha error or the probability of rejecting the correct null hypothesis.

Level of significance : It is the probability of committing a ______ error or ______ error or the probability of rejecting the correct null hypothesis.

In hypothesis testing, 100% accuracy is ____ possible for accepting or rejecting a _____ hypothesis. So, we therefore select a level of significance that is usually 1% and 5%. Level of significance is the maximum probability of committing a _________That is, ___ = 𝛼. This probability is symbolized by 𝛼(_______ letter _____).

________ the significance level is chosen, a ____________ is selected from a table for the appropriate test statistic.

The __________ determines the critical and noncritical regions.

The ______________ is a value that separates the critical region from the noncritical region.

The critical or rejection region is the range of the values of the test value that indicates that there is __________ difference and that the _____ hypothesis (H0) should be _________.

The ________ or ________ region is the range of the values of the test value that indicates that there is significant difference and that the null hypothesis (H0) should be rejected.

____________or ___________ region is the range of the values of the test value that indicates that the difference was probably due to chance and that the null hypothesis (H0) should not be rejected.

Noncritical or nonrejection region is the range of the values of the test value that indicates that the difference was probably due to chance and that the ______ hypothesis (H0) should ____ be _________

_______________ is the probability of not committing a Type II error or beta error

The ____________ is used as a basis for deciding whether to reject or accept the null hypothesis.

The rejection region lies at ________ the left or right tail of the normal curve if _____ tailed test is being used. On the other hand, the rejection region lies at _____ end tails of the normal curve if _____ tailed test will be utilized.

When the test statistic lies on the rejection region, then the null hypothesis will be __________.

The _____________ region is the probability of making a Type I error equals to the level of significance.

The non-rejection region is the probability of making a ________ error _______ to the level of ____________..

Non-rejection region is also known as the _________ region.

When the statistic lies within the non-rejection region, the _____ hypothesis will be __________ or the critical value is _________ than the computed value of the test statistic.

When the statistic lies within the ____________ region, the null hypothesis will be accepted or the _________ value is greater than the _________ value of the test statistic.

The ____________ is a value that separates the non-rejection region and the rejection region.

The use of one-tailed test or two-tailed test will depend on how the ___________ is formulated. If the alternative hypothesis is expressed in _____________, it will utilize the two-tailed test. However, use the one-tailed test if the _________ hypothesis is ____________.

In two-tailed test, the two _________ regions lie at ______ end tails of the normal curve; each part will be half of the ________ value. If alpha = 0.05, the area in each end tail is alpha=0.025. In one-tailed test, the rejection region lies ________ at the left or right end tail of the normal curve.

A one-tailed test shows that the _____ hypothesis be ________ when test value is in critical region on _____ side of the mean.

________________ is a type of statistical inference, which examines the claim about a population based on the information obtained in the random sample.