## say that we "fail to reject the null hypothesis", ..

### Is a p-value of 0.04993 enough to reject null hypothesis?

Basically, you reject the null hypothesis when your test value falls into the . There are four main ways you’ll compute test values and either support or reject your null hypothesis. Which method you choose depends mainly on if you have a proportion or a .

### Is a p-value of 0.04993 enough to reject null hypothesis

The decision rule is a statement that tells under what circumstances to reject the null hypothesis. The decision rule is based on specific values of the test statistic (e.g., reject H_{0} if Z __>__ 1.645). The decision rule for a specific test depends on 3 factors: the research or alternative hypothesis, the test statistic and the level of significance. Each is discussed below.

3. Using the data from sample 3, perform a hypothesis test on the sample data using a significance level of 0.01. Answer the following questions below:

a. What is the sample mean and sample standard deviation?

b. What is the p-value

c. Do you accept the null hypothesis or reject the null hypothesis?

d. Should any action be taken?

## why do you reject the null hypothesis when the p-value is ..

We have already seen how to do the first step, and have null and alternate hypotheses. The second step involves the calculation of the *t*-statistic for one mean, using the formula:

## Accepting versus not rejecting the null hypothesis - …

1. Using the data from sample 1, perform a hypothesis test on the sample data using a significance level of 0.01. Answer the following questions below:

a. What is the sample mean and sample standard deviation?

b. What is the p-value

c. Do you accept the null hypothesis or reject the null hypothesis?

d. Should any action be taken?

## Accepting versus not rejecting the null hypothesis

Using the .05 level of significance means if the null hypothesis is true, we would get our result 5 times out of 100 (or 1 out of 20). We take the risk that our study is *not* one of those 5 out of 100. Rejecting or accepting the null hypothesis is a gamble. There is always a possibility that we are making a mistake in rejecting the null hypothesis. This is called a - rejecting the null hypothesis when it is true. If we use a .01 cutoff, the chance of a Type I Error is 1 out of 100. With a .05 level of significance, we are taking a bigger gamble. There is a 1/20 (5 out of 100) chance that we are wrong, and that our treatment (or predictor variable) doesn't really matter.

## you reject the null hypothesis and accept an ..

The null hypothesis is essentially the "devil's advocate" position. That is, it assumes that whatever you are trying to prove did not happen (*hint:* it usually states that something equals zero). For example, the two different teaching methods did not result in different exam performances (i.e., zero difference). Another example might be that there is no relationship between anxiety and athletic performance (i.e., the slope is zero). The alternative hypothesis states the opposite and is usually the hypothesis you are trying to prove (e.g., the two different teaching methods did result in different exam performances). Initially, you can state these hypotheses in more general terms (e.g., using terms like "effect", "relationship", etc.), as shown below for the teaching methods example:

## 08/08/2008 · Do we reject/accept the null Ho ..

We call the blueareas the since if thevalue of falls in these regions, we can say that the null hypothesis is veryunlikely so we can **Example** smokers were questioned about the number of hoursthey sleep each day.