## How do you write the results of Shapiro Wilk test?

When reporting the Shapiro-Wilk test, the following should be mentioned:

- The reason why the test was used.
- The results of the test: the value of the test statistic W and the p-value associated with it.
- The consequences/interpretation of these results.

## Can I do a Shapiro Wilk test in Excel?

Setting up a Shapiro-Wilk and other normality tests Select the XLSTAT / Describing data / Normality tests, or click on the corresponding button of the Describing data menu. Once you’ve clicked on the button, the dialog box appears. Select the two samples in the Data field.

**How do you interpret the value of Shapiro Wilk test?**

In the Shapiro-Wilk W test, the null hypothesis is that the sample is taken from a normal distribution. This hypothesis is rejected if the critical value P for the test statistic W is less than 0.05. The routine used is valid for sample sizes between 3 and 2000.

**How do you perform a Shapiro test in Python?**

How to Perform Shapiro-Wilk test in Python?

- If the p-value ≤ α, then we reject the null hypothesis i.e. we assume the distribution of our variable is not normal/gaussian.
- If the p-value > α, then we fail to reject the null hypothesis i.e. we assume the distribution of our variable is normal/gaussian.

### How do you do a Shapiro test in Excel?

How to Perform a Shapiro-Wilk Test

- Click BASIC STATISTICS.
- Choose NORMALITY TEST.
- Type your data column in the VARIABLE BOX (do not fill in the reference. box)
- Choose RYAN JOINER (this is the same as Shapiro-Wilk)
- Click OK.

### What if the Shapiro-Wilk test is not significant?

The Shapiro-Wilk test is a statistical test of the hypothesis that the distribution of the data as a whole deviates from a comparable normal distribution. If the test is non-significant (p>. 05) it tells us that the distribution of the sample is not significantly different from a normal distribution.

**How do you test if a distribution is normal?**

For quick and visual identification of a normal distribution, use a QQ plot if you have only one variable to look at and a Box Plot if you have many. Use a histogram if you need to present your results to a non-statistical public. As a statistical test to confirm your hypothesis, use the Shapiro Wilk test.

**How do you test if sample is normally distributed?**

The most common graphical tool for assessing normality is the Q-Q plot. In these plots, the observed data is plotted against the expected quantiles of a normal distribution. It takes practice to read these plots. In theory, sampled data from a normal distribution would fall along the dotted line.