Difference between revisions of "Data Screening"

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(Created page with "== 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 the...")
 
(Data Screening)
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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" (Lawrence, Gamst, & Guarino, 2017, p. 31).
 
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" (Lawrence, Gamst, & Guarino, 2017, p. 31).
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Contribution by: Britany Kuslis, WCSU Cohort 8
 
Contribution by: Britany Kuslis, WCSU Cohort 8
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Reference
 
Reference
 
Lawrence, S., Gamst, G, & Guarino, A.J. (2017). ''Applied multivariate research: Design and interpretation.'' Thousand Oaks, CA: Sage Publications.
 
Lawrence, S., Gamst, G, & Guarino, A.J. (2017). ''Applied multivariate research: Design and interpretation.'' Thousand Oaks, CA: Sage Publications.
 
  
 
== Data Cleaning ==
 
== Data Cleaning ==

Revision as of 18:54, 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" (Lawrence, Gamst, & Guarino, 2017, p. 31).


Contribution by: Britany Kuslis, WCSU Cohort 8

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

Data Cleaning