Managing Technology Transition in Saudi Arabia by Khalid A. Alrashoud

Author:Khalid A. Alrashoud
Language: eng
Format: epub
ISBN: 9789811558030
Publisher: Springer Singapore

4.4.3 Date Analysis

Reliability testing across the four innovation attributes scales was conducted to check the internal consistency of the acquired set data. Normality testing was done to determine the appropriate statistical methods for data analysis (parametric or nonparametric tests). Shapiro–Wilk test and Kolmogorov–Smirnov tests are recommended in the literature for testing normality as they are superior in power for detecting significant deviations from normality (D’Agostino and Stephens 1986). These tests provide statistically significant results (p < 0.05) whenever the distribution of the numerical variable significantly differs from the normal distribution (D’Agostino and Stephens 1986). Nonparametric distributions are best described with the median for central tendency, the interquartile range for dispersion and the Mann-Whitney U test for comparing different medians with statistical significance. Furthermore, Spearman’s rho rank correlation coefficient test was calculated to determine the rank correlation between the variables (Lehman et al. 2005). Further, the mean scores of the questions per attribute were calculated along with the frequencies and proportion for each question to identify the important variables in respondents’ attitudes. The chi-squared test and Fisher exact test were used to compare the categorical variables. The corresponding p-value was calculated for each statistical test, where results with a p-value of less than 0.05 were considered to be statistically significant, and results with a p-value of less than 0.01 were considered to be highly significant.

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