Improving Multivariate Analysis in Career and Technical Education by Screening Data: Don’t Just Assume Assumptions Are Met

• In Event: Career and Technical Education Research to Improve Teaching and Learning

Abstract

The use of prescreening data procedures in published research in career and technical research over the last five years was examined. Information showed a lack of consistency in reporting or a lack of reporting prescreening data techniques using various statistical methods. Showing the need for continuous improvement in research methods and reporting of research methods. The following will describe a step by step process of pre-screening data missing data, outliers, normality, linearity, and homoscedasticity at the univariate level and then outliers, normality, linearity and homoscedasticity at the multivariate level.

Authors

• Tara K. Shollenberger, High Point University

• James E. Bartlett, North Carolina State University