Learn How to Identify and Manage Outliers in Datasets From the General Social Survey (2018) Using IBMSPSS / Julie Scott Jones.

Format:

Book

Author/Creator:

Jones, Julie Scott, author.

Language:

English

Subjects (All):

Quantitative research.

Physical Description:

1 online resource : illustrations

Place of Publication:

London : SAGE Publications Ltd, 2025.

Summary:

This dataset is designed for learning how to identify and manage outliers in datasets prior to their use for either descriptive and/or inferential analysis. The identification and management of outliers, especially with scale data, should be the first thing that you do with a dataset before any further data cleaning or analysis, failure to overlook this step will mean that you cannot rely on your later analysis, as it may be skewed. This guide will outline the key reasons for identifying and managing outliers in a dataset. Relatedly it will show how to identify and manage outliers in scale data. The dataset is a subset of data derived from the 2018 General Social Survey. The dataset file is accompanied by a student guide, and a how to guide for IBM® SPSS®.

Notes:

Description based on publisher supplied metadata and other sources.

ISBN:

1-03-622210-1

9781036222109

OCLC:

1523171199