## What is a good statistical question?

A statistical question is one for which you don’t expect to get a single answer. For example, “How tall are you?” is not a statistical question. But “How tall are the students in your school?” is a statistical question.

## What are the basic statistics?

The most common basic statistics terms you’ll come across are the mean, mode and median. These are all what are known as “Measures of Central Tendency.” Also important in this early chapter of statistics is the shape of a distribution.

## What is the P value in statistics?

The p-value is a number, calculated from a statistical test, that describes how likely you are to have found a particular set of observations if the null hypothesis were true. P-values are used in hypothesis testing to help decide whether to reject the null hypothesis.

## What does P value of 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.

## Is P 0.01 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).

## What is a 0.01 significance level?

Typical values for are 0.1, 0.05, and 0.01. These values correspond to the probability of observing such an extreme value by chance. In the test score example above, the P-value is 0.0082, so the probability of observing such a value by chance is less that 0.01, and the result is significant at the 0.01 level.

## Is P 02 statistically significant?

For example, a p-value of . 02 means that, assuming that the treatment has no effect, and given the sample size, an effect as large as the observed effect would be seen in only 2% of studies. 05, then a p-value of . 05 or less is required to reject the null hypothesis and establish statistical significance.

## How do you know if t statistic is significant?

As an example if your level of significance is 0.05, the correspondent t-stat value is 1.96, thus when the t-stat reported in the output is higher than 1.96 you reject the null hypothesis and your coefficient is significant at 5% significance level.

## What is the difference between P-value and Alpha?

Alpha sets the standard for how extreme the data must be before we can reject the null hypothesis. The p-value indicates how extreme the data are. 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.

## What if P-value is less than alpha?

If your p-value is less than your selected alpha level (typically 0.05), you reject the null hypothesis in favor of the alternative hypothesis. If the p-value is above your alpha value, you fail to reject the null hypothesis.