Contents
Do outliers affect the p value?
2, with three outlier samples or less, power increases as effect size increases in the distribution-based p-value, the outlier robust t-statistic, and the outlier sum approaches, but not in the other two approaches for both normal and t-distributions. The distribution-based p-value approach performs best in most cases.
Can you do at test with outliers?
In particular, you need to make sure that the presence of outliers does not distort the results. For the t-test on independent samples, the data in each sample must be normal or at least reasonably symmetric and that the presence of outliers does not distort either of these results.
How do outliers affect the results of a t-test?
Sheskin (2000) states that the presence of one or several outliers can have a substantial effect on both the mean and the variance of a distribution. If the variance is impacted by outliers test-statistics might not be reliable. However, the outliers in his study are fixed to a single, rather extreme value.
Which is an example of an outlier test?
The engineer records the force that is required to break each handle. The engineer creates a graph of the data and notices that one of the values in the sample seems unusually small. The engineer performs an outlier test to determine whether the smallest value is an outlier. Open the sample data, HandleStrength.MTW.
Which is smallest data value is an outlier?
(Alternative hypothesis), select Smallest data value is an outlier. Click OK in each dialog box. The mean of the sample is 123.4. The G statistic indicates that the smallest data value, 12.38, is 2.4 standard deviations less than the mean.
When to reject the null hypothesis in normality test?
If the p-value is less than or equal to the significance level, the decision is to reject the null hypothesis and conclude that your data do not follow a normal distribution. If you plan to analyze data that don’t follow a normal distribution, check the data requirements for the analysis.
How to determine if data do not follow a normal distribution?
To determine whether the data do not follow a normal distribution, compare the p-value to the significance level. Usually, a significance level (denoted as α or alpha) of 0.05 works well.