### Checking for Outliers

SPSS Survival Manual by Julie Pallant: Many statistical techniques are sensitive to outliers. The previous techniques that we have talked about under the descriptive section can also be used to check for outliers. However, there is alternative way to assess them.

Procedure for Identifying Outliers:

- From the menu at the top of the screen, click on
**Analyze**, then click on**Descriptive Statistics**, then**Explore**. - In the
**Display**section, make sure**Both**is selected. This provides both**Statistics**and**Plots**. - Click on your variable (e.g. most important problems in 12 months), and move it into the
**Dependent list**box. - Click on id from your variable list and move into the section
**Label cases**. This will give you the ID number of the outlying case. - Click on the
**Statistics**button. Click on**Outliers**. Click on**Continue**. - Click on the
**Plots**button. Click on**Histogram**. Ask for a**Stem**and**Leaf plot**as well. - Click on the
**Options**button. Click on**Exclude cases pairwise**. Click on**Continues**and then**OK**.

The output generated from this analysis as follows:

Reading the Output:

- Have a look at the Histogram and check the tails of distribution if there are data points falling away as the extremes.
- Inspect the Boxplot whether SPSS identifies outliers. These outliers are displayed as little circles with a ID number attached.
- Make sure that the outlier's score is genuine and not an error.
- Descriptive table provide you with an indication of how much a problem associated with these outlying cases. The expected value is the 5% Trimmed Mean. SPSS removes the top and bottom 5 per cent of the cases and calculated a new mean value to obtain this Trimmed Mean value. If you compare the original mean and this new trimmed mean, you can see if your more extreme scores are having a lot of influence on the mean. If you find these two mean values are very different, you need to investigate the data points further.
- The Extreme values table gives you with the highest and the lowest values recorded for that variable and also provide the ID of the person with that score. It helps to identify the case that has the outlying values. SPSS Survival Manual by Julie Pallant

## 12 comments:

This was very informative and to the point. Excellent!

This Was Really Helpful Thanks ....

sooooo helpful!!!!

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Great article, extremely helpful. Thank you!

Excellent !!! Thanks a lot !!

THANK YOU!!!

Hi, thanks for this info! Question: How does one define "very different?"

"...If you find these two mean values are very different, you need to investigate the data points further."

Hi,

Thanks for this! How do you define "very different?"

"...If you find these two mean values are very different, you need to investigate the data points further."

Hi,

Thanks for this! How do you define "very different?"

"...If you find these two mean values are very different, you need to investigate the data points further."

excellent!

For my data set, all outliers disappeared when I changed the scale of the y-axis from linear to log. What happened?

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