## For which of the given p values would the null hypothesis be rejected when performing a level 0.05 test?

We **reject** the **null hypothesis** when the **p**–**value** is less than α. For example if the **p**–**value** = 0.08, then we **would** fail to **reject** H0 at the significance **level** of α=**0.05** since 0.08 > **0.05**, but we **would reject** H0 at the significance **level** of α = 0.10 since 0.08 < 0.10.

## When P value is greater than alpha We do not reject the null hypothesis?

If the **p**–**value is less than or equal** to the **alpha** (**p**<. 05), **then we reject the null hypothesis**, and **we** say the result is statistically significant. If the **p**–**value is greater than alpha** (**p** >. 05), **then we** fail to **reject the null hypothesis**, and **we** say that the result is statistically nonsignificant (n.s.).

## Does statistically significant means reject null hypothesis?

After you perform a **hypothesis** test, there are only two possible outcomes. When your p-value **is** less than or equal to your **significance** level, you **reject** the **null hypothesis**. Your results are **statistically significant**. When your p-value **is** greater than your **significance** level, you fail to **reject** the **null hypothesis**.

## Is P 0.1 statistically significant?

Conventionally the 5% (less than 1 in 20 chance of being wrong), 1% and **0.1**% (**P** < 0.05, 0.01 and 0.001) levels have been used. Most authors refer to **statistically significant** as **P** < 0.05 and **statistically** highly **significant** as **P** < 0.001 (less than one in a thousand chance of being wrong).

## How do you know to reject or fail to reject?

Suppose that you do a hypothesis test. Remember that the decision to **reject** the null hypothesis (H _{}) or **fail to reject** it can be based on the p-value and your chosen significance level (also called α). If the p-value is less than or equal to α, you **reject** H _{}; if it is greater than α, you **fail to reject** H _{}.

## Why reject null hypothesis when p value is small?

A crucial step in **null hypothesis** testing is finding the likelihood of the sample result if the **null hypothesis** were true. This probability is called the **p value**. A low **p value** means that the sample result would be unlikely if the **null hypothesis** were true and leads to the **rejection** of the **null hypothesis**.

## What does P value of 1 mean?

Popular Answers (**1**)

When the data is perfectly described by the resticted model, the probability to get data that is less well described is **1**. For instance, if the sample **means** in two groups are identical, the **p**–**values** of a t-test is **1**.

## What does P value tell you?

The **p**–**value**, or probability **value**, **tells you** how likely it is that your data could have occurred under the null hypothesis. The **p**–**value** is a proportion: if your **p**–**value** is 0.05, that means that 5% of the time **you** would see a test statistic at least as extreme as the one **you** found if the null hypothesis was true.

## What is p value formula?

The **p**–**value** is calculated using the sampling distribution of the test statistic under the null hypothesis, the sample data, and the type of test being done (lower-tailed test, upper-tailed test, or two-sided test). The **p**–**value** for: an upper-tailed test is specified by: **p**–**value** = **P**(TS ts | H _{} is true) = 1 – cdf(ts)

## What does p value 0.05 mean?

**P** > **0.05 is the** probability that the null hypothesis is true. A statistically significant test result (**P** ≤ **0.05**) **means** that the test hypothesis is false or should be rejected. A P **value** greater than **0.05 means** that no effect was observed.

## How should you interpret a decision that fails to reject the null hypothesis?

There is enough evidence to **reject** the claim. e) **How should you interpret a decision that fails to reject the null hypothesis**? There is not enough evidence to **reject** the claim.

## When the null hypothesis is false?

If the **null hypothesis is false**, there is a 1-β probability that we will make the right choice and reject it. The probability that we will make the right choice **when the null hypothesis is false** is called statistical power.

## What if P value is 0?

Hello, **If** the statistical software renders **a p value** of 0.000 it means that the **value** is very low, with many “” before any other digit. In SPSS for example, you can double click on it and it will show you the actual **value**.

## What does a significance level of 0.01 mean?

The lower the **significance level**, the more the data must diverge from the null hypothesis to be **significant**. Therefore, the **0.01 level** is more conservative than the 0.05 **level**. The Greek letter alpha (α) is sometimes used to indicate the **significance level**.

## What is the 10 significance level?

Popular **levels** of **significance** are **10**% (0.1), 5% (0.05), 1% (0.01), 0.5% (0.005), and 0.1% (0.001). If a **test** of **significance** gives a p-value lower than or equal to the **significance level**, the null hypothesis is rejected at that **level**. The lower the **significance level** chosen, the stronger the evidence required.