Several things can be done to the raw data to see what it can say about hypotheses (Neuman, 2003). An inspection of the raw data can be done using descriptive statistics to find obvious coding errors. The minimum and maximum values ​​of each variable must be within the allowed range. Pairwise correlations describe that all relationships must be in the expected direction. Meanwhile, listwise deletion of missing values ​​indicates that the data can be used for analysis. An outlier is an unusually small or large observation. Outliers help researchers detect coding errors. According to Bagozzi and Baumgartner (1994), it is not advisable to routinely exclude outliers from further analyses. The collected data were analyzed using three approaches:1. Cronbach's alpha (a) was used to test reliability. Cronbach's alpha indicates how well the elements of a set are positively correlated with each other. This is to ensure that the scales are free from random or unstable errors and produce consistent results over time (Cooper & Schindler, 1998);2. Descriptive statistics where the researcher used mean, standard deviation and variance to get an idea of ​​how the respondents reacted to the questionnaire items. The primary concern of descriptive statistics is to present information in a convenient, usable, and understandable form (Runyon & Audry, 1980). Descriptive summary, including frequency and description, was used to examine the data set. Among the basic statistics to be used were mean, median, mode, sum, variance, range, minimum, maximum, skewness, and kurtosis.3. Inferential statistics concerning the generalization of a sample to make estimates and inferences about a larger population (Neuman, 2003...... half of the paper ....... i.e. more than 30 (Hair et al., 2006) Sekaran (2003) suggests that the approximation to normality of the observed variables could be studied by examining the data through histograms, stem and leaf displays, probit plots, and by calculating univariate and multivariate measures of skewness and kurtosis the leaf and probit plots indicate the distribution symmetric of variables or sets of variables. Chou and Fidell (1996) suggest that the value of skewness and kurtosis is equal to zero if the distribution of a variable is normal and Chou and Bentler (1995) emphasizes the absolute values ​​of skewness indices. univariates above 3 can be described as extremely skewed, while a kurtosis threshold value above 10 can be considered problematic and a value above 20 can be considered as having serious problems (Hoyle, 1995; Kline, 1998).