Identify Outliers using Stem-and-leaf Plot and Boxplots in SPSS
Titocan Mark Solutions Titocan Mark Solutions
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 Published On Sep 1, 2021

In this video, I demonstrated how to use Stem-and-leaf plots and the Boxplots respectively to identify outliers in dataset using SPSS statistical package. This video provides better illustration that are explicitly simple to replicate and supported by perfect Interpretations of the outcome.

Outliers are unwanted observed data values that can affect results of the data analysis, by giving unrealistic and deceptive outcomes. So, it is imperative that you learn how to identify Outliers in your dataset and eliminate them from the dataset before you proceed to analyze the data.

In my previous video, I used the Tukey's Hinges approach in SPSS to identify Outliers in the same dataset used in this video, and if you had seen that video, you would note that the identified Outliers in that video are the same as in this video. That means you can use either the:

1. Tukey's Hinges approach,
2. Stem-and-leaf Plot approach, or
3. Boxplots approach

To identify Outliers in your dataset. The choice of any approach to use is entirely at your prerogative, because all the approaches are individually reliable.

In my next video, I will be demonstrating how to use Scattered Plot to identify outliers using this same dataset. Please, SUBSCRIBE now to be notified when the video is published.

VIDEO LINKS:
Identify Outliers using Tukey's Hinges Approach in SPSS:    • Identify Outliers using Tukey's Hinge...  

To learn how to load data into SPSS, please kindly see my video on:
Introduction to SPSS Software for Beginners Part-1:    • Introduction to SPSS Software for Beg...  

Introduction to SPSS Software for Beginners Part-2:    • Introduction to SPSS Software for Beg...  


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