The correct answer is "sometimes be rejected at the 1% level".

Here's why:

The level of significance, often denoted by alpha (α), is the probability of rejecting the null hypothesis when it is true. In other words, it's the likelihood of making a Type I error.

If a hypothesis is not rejected at a 5% level of significance, it means that the test statistic calculated from the sample data falls within the acceptance region defined by the 5% level of significance.

However, when we lower the level of significance to 1%, we are essentially making the acceptance region narrower. This means that it's possible for the test statistic to now fall outside the acceptance region, leading to the rejection of the null hypothesis.

Therefore, a hypothesis that is not rejected at a 5% level of significance can sometimes be rejected at a 1% level of significance, depending on the specific value of the test statistic.

Question

The correct answer is "sometimes be rejected at the 1% level".

Here's why:

The level of significance, often denoted by alpha (α), is the probability of rejecting the null hypothesis when it is true. In other words, it's the likelihood of making a Type I error.

If a hypothesis is not rejected at a 5% level of significance, it means that the test statistic calculated from the sample data falls within the acceptance region defined by the 5% level of significance.

However, when we lower the level of significance to 1%, we are essentially making the acceptance region narrower. This means that it's possible for the test statistic to now fall outside the acceptance region, leading to the rejection of the null hypothesis.

Therefore, a hypothesis that is not rejected at a 5% level of significance can sometimes be rejected at a 1% level of significance, depending on the specific value of the test statistic.

Knowee AI · Accepted Answer

The correct answer is "sometimes be rejected at the 1% level".

Here's why:

The level of significance, often denoted by alpha (α), is the probability of rejecting the null hypothesis when it is true. In other words, it's the likelihood of making a Type I error.

If a hypothesis is not rejected at a 5% level of significance, it means that the test statistic calculated from the sample data falls within the acceptance region defined by the 5% level of significance.

However, when we lower the level of significance to 1%, we are essentially making the acceptance region narrower. This means that it's possible for the test statistic to now fall outside the acceptance region, leading to the rejection of the null hypothesis.

Therefore, a hypothesis that is not rejected at a 5% level of significance can sometimes be rejected at a 1% level of significance, depending on the specific value of the test statistic.

If a hypothesis is not rejected at a 5% level of significance, it will ___.Group of answer choicesalso not be rejected at the 1% levelalways be rejected at the 1% levelsometimes be rejected at the 1% levelNot enough information is given to answer this question

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