Preliminary Data Analysis: An Analysis Before the Analysis

Saiyidi Mat Roni () and Hadrian Geri Djajadikerta ()
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Saiyidi Mat Roni: Edith Cowan University, School of Business and Law
Hadrian Geri Djajadikerta: Edith Cowan University, School of Business and Law

Chapter Chapter 3 in Data Analysis with SPSS for Survey-based Research, 2021, pp 15-54 from Springer

Abstract: Abstract We dedicate this one whole chapter for data prep. We walk you through the chronological steps to prepare your data before you run any major test to answer your research questions. In this chapter, we walk you through the processes needed to clean your dataset. We begin with identifying the monotonous responses. These are the ones that have no variations (more on this in the chapter). We also teach you how to deal with missing values and outliers, and of course, testing if the data is normally distributed. SPSS will run the tests you ask and give you outputs regardless of the state of the dataset. But, you need to be confidence to say that the outputs are correct. If the data is wrong, then the outputs are questionable. Afterall, if you put in diesel for your car that runs on a petrol, the engine most probably runs but you may not reach the destination (and a costly repair ensues).

Keywords: Expected maximisation; Missing value analysis; Monotone; Multiple imputation; Normal distribution; Outlier; Reliability; Validity (search for similar items in EconPapers)
Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-981-16-0193-4_3

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DOI: 10.1007/978-981-16-0193-4_3

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