Analysis Of The Point Scale Range: An Inference On Optimal Point Scale Range

Abstract

The objective of this study is to systematically analyze and statistically prove whether the internal consistency level of the data characteristics (normal distribution, skewness, and kurtosis) is sensitive to the point scale range of the correlation coefficients and covariance matrices. The research was carried out using three different data sets obtained by applying the convenience sampling method on students studying at Eskişehir Osmangazi University, Faculty of Economics and Administrative Sciences. According to the results, the internal consistency level increases when the point scale range increase; and, the difference between 5-point scale and 11-point scale was observed to be statistically significant. Furthermore, the inter-scales correlation coefficient was determined to increase systematically; however, this increase was found not to be statistically significant. It was also observed that the inter-variable covariance matrices change significantly based on the point scale range; yet the path coefficients in covariance-based structural equation modeling do not change significantly.