An Empirical Study on the Transformation of Likert-scale Data to Numerical Scores
نویسنده
چکیده
The application of statistical methods to data analysis requires that the data set concerned should follow some particular assumptions. For example, AVOVA assumes that the response variable is normally distributed within groups, and the variances in the different groups are identical. However such assumptions are generally not observed by data collected through Likert Scales. This paper presents a computation procedure for transforming Likert-scale data into numerical scores that better follow the assumption of normality, based on the scaling procedure proposed by E. J. Snell. We have also conducted an empirical study to investigate the effects of the proposed transformation on data analysis. Finally this paper addresses the decision on whether or not that Likertscale data should be transformed to scores that are more compliant to statistical assumptions. Mathematics Subject Classification: 62P25
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