Table of Contents

## How do you reject the null hypothesis with z-score?

If the value of z is greater than 1.96 or less than -1.96, the null hypothesis is rejected. The value for z is calculated by subtracting the value of the average daily return selected for the test, or 1% in this case, from the observed average of the samples.

## How do you interpret p-value from z-score?

The p-value associated with a 95% confidence level is 0.05. If your Z score is between -1.96 and +1.96, your p-value will be larger than 0.05, and you cannot reject your null hypothesis….Results

- p < 0.1, the hypothesis is rejected.
- 0.1
- p>0.1, the hypothesis is accepted.

**How do you know if p-value is rejected?**

If the p-value is less than or equal to the specified significance level α, the null hypothesis is rejected; otherwise, the null hypothesis is not rejected. In other words, if p≤α, reject H0; otherwise, if p>α do not reject H0.

**At what p-value do you accept the null hypothesis?**

One of the most commonly used p-value is 0.05. If the calculated p-value turns out to be less than 0.05, the null hypothesis is considered to be false, or nullified (hence the name null hypothesis). And if the value is greater than 0.05, the null hypothesis is considered to be true.

### How do you find the z-score and rejection region?

When α is 0.025, Z is 1.96. So, 1.96 on the right side and minus 1.96 on the left side. Therefore, if the value we get for Z from the test is lower than minus 1.96, or higher than 1.96, we will reject the null hypothesis.

### What do you need to do with the p-value when using Z in a two-tailed test?

In the case of a two-tailed z-test, “more extreme” means having a z-value at least as great in magnitude (at least as far from zero) as the observed z-value. So if your sample gives a z-value of say 1.3 (just for an example), then the p-value will be the area to the right of 1.3 plus the area to the left of -1.3.

**What z-score is significant?**

A sample mean with a z-score greater than or equal to the critical value of 1.645 is significant at the 0.05 level. There is 0.05 to the right of the critical value. DECISION: The sample mean has a z-score greater than or equal to the critical value of 1.645. Thus, it is significant at the 0.05 level.

**What does fail to reject the null hypothesis mean?**

When we fail to reject the null hypothesis when the null hypothesis is false. The “reality”, or truth, about the null hypothesis is unknown and therefore we do not know if we have made the correct decision or if we committed an error.

#### What is the difference between the p-value and z score?

The p-value is a worst-case bound on that probability. The p-value can be thought of as a percentile expression of a standard deviation measure, which the Z-score is, e.g. a Z-score of 1.65 denotes that the result is 1.65 standard deviations away from the arithmetic mean under the null hypothesis.

#### What is the critical z score of the null hypothesis?

Unless otherwise stated, we can assume an alpha level of 0.05. This gives us a critical Z score of: 1.64 Now we must decide whether to reject the Null hypothesis or fail to reject the null hypothesis.

**What is the z score of a 1 tailed hypothesis?**

From the stated hypothesis, we know that we are dealing with a 1-tailed hypothesis test. Unless otherwise stated, we can assume an alpha level of 0.05. This gives us a critical Z score of: 1.64 Now we must decide whether to reject the Null hypothesis or fail to reject the null hypothesis.

**Can you reject the null hypothesis in a one-tailed test?**

So we would have rejected the null hypothesis for both one-tailed tests, but we would have failed to reject the null in the two-tailed test. If, however, we’d picked a more rigorous α = 0. 0 5 \\alpha=0.05 α = 0. 0 5 or α = 0. 0 1 \\alpha=0.01 α = 0. 0 1, we would have failed to reject the null hypothesis every time.