Difference between revisions of "Data Screening"

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(Data Screening)
(Causes of Outliers)
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== Causes of Outliers ==
 
== Causes of Outliers ==
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== Detection of Multivariate Outliers ==
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== Detection of Multivariate Outliers: Scatterplot Matrices ==
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== Detection of Multivariate Outliers: Mahalanobis Distance ==

Revision as of 18:07, 16 November 2019

Data Screening

Once data from a research study is gathered and has been entered into SPSS, researchers must examine their data to be sure they can validly interpret their results. Valid interpretation of data is reliant on two data features:

1. The data must meet the assumptions of the analysis procedure.

2. The data in the data file are "an accurate representation or transcription of what was provided by research participants as their original responses or what was provided by archival sources as original data" (Meyers, Gamst, & Guarino, 2017, p. 31).


Contribution by: Britany Kuslis, WCSU Cohort 8

Reference:

Meyers, L., Gamst, G., & Guarino, A.J. (2017). Applied multivariate research: Design and interpretation. Thousand Oaks, CA: Sage Publications.


Data Cleaning

Value Cleaning

Outliers

Causes of Outliers

Detection of Multivariate Outliers

Detection of Multivariate Outliers: Scatterplot Matrices

Detection of Multivariate Outliers: Mahalanobis Distance