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

Sage Research Methods Data and Research Literacy 2025 Available online

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Format:
Book
Author/Creator:
Jones, Julie Scott, author.
Language:
English
Subjects (All):
Quantitative research--Data processing.
Quantitative research.
Physical Description:
1 online resource
Place of Publication:
London : SAGE Publications Ltd, 2025.
Summary:
This dataset is designed for learning how to identify and remove errors in datasets prior to their use for either descriptive and/or inferential analysis. The identification and removal of errors 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, and you may create further errors in your work. This guide will outline the key reasons for identifying and removing errors in a dataset. Relatedly it will show how to identify and remove errors in different types of 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:
1-03-622209-8
9781036222093
OCLC:
1523169600

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