Descriptive statistics outliers

Example: Using The Interquartile Range to Find Outliers

We’ll walk you through the popular IQR method for identifying outliers using a step-by-step example. Your dataset has 11 values

Dealing with Outliers

Once you’ve identified outliers, you’ll decide what to do with them. Your main options are retaining or removing them from your dataset

How are outliers determined in statistics?

Outliers are data values that differ greatly from the majority of a set of data

These values fall outside of an overall trend that is present in the data

A careful examination of a set of data to look for outliers causes some difficulty

What are outliers in data cleansing?

Some outliers represent true values from natural variation in the population

Other outliers may result from incorrect data entry, equipment malfunctions, or other measurement errors

An outlier isn’t always a form of dirty or incorrect data, so you have to be careful with them in data cleansing

What is an outlier in SPSS?

An outlier is an observation that lies abnormally far away from other values in a dataset

Outliers can be problematic because they can effect the results of an analysis

This tutorial explains how to identify and handle outliers in SPSS

Suppose we have the following dataset that shows the annual income (in thousands) for 15 individuals:

Sort your data from low to high
Identify the first quartile (Q1), the median, and the third quartile (Q3).
Calculate your IQR = Q3 – Q1
Calculate your upper fence = Q3 + (1.5 * IQR)
Calculate your lower fence = Q1 – (1.5 * IQR)

Often, outliers are easiest to identify on a boxplot. On a boxplot, asterisks (*) denote outliers. Try to identify the cause of any outliers. Correct any data–entry errors or measurement errors. Consider removing data values for abnormal, one-time events (also called special causes). Then, repeat the analysis.In descriptive statistics, a boxplot is used for explanatory data analysis to show the outliers in a dataset. A boxplot is constructed by drawing box between the upper and lower quartiles with a solid line drawn across the box to locate the median. Any number that is above the upper fence or below lower fence is said to be an outlier.Steps for making a box plot (with outliers) Draw the box between Q1 and Q3 Accurately plot the median Determine possible outliers that are more than 1.5 interquartile ranges from the box. Lower Inner Fence = Q1 – (1.5)IQR Upper Inner Fence = Q3 + (1.5)IQR Mark outliers with a special character like a * or •.

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