3.5       Data Analysis

            The data will be extracted from the questionnaires and will be analysed by using Statistical Package for Social Science (SPSS 20.0 version). 

            3.5.1   Empirical Analysis

Through empirical analysis, it is a way of gaining the knowledge by means of direct and indirect observation which can be analysed quantitatively or qualitatively. The analysis of the research data will include Reliability Statistics Analysis, Descriptive Analysis, Pearson Correlation Analysis, and Regression Analysis.

3.5.1.1            Reliability Statistics Analysis.

Reliability is an indication of the stability and consistency with the instrument measures the concept and helps to assess the free error of a measure (Sekaran & Bougie 2010).  Reliability of the measures was tested using Cronbach‟s Alpha.  It is reliability coefficient that investigates how the variables are positively correlated with other variables.  According to Sekaran & Bougie (2010), reliability test was applied to ensure consistency in measurement across time and various items in the instrument.  The closer the Cronbach‟s Alpha is to 1, the higher the internal consistency reliability (Sekaran & Bougie, 2010). Reliability less than 0.60 are considered to be poor, those between 0.60 and 0.70 range is considered as acceptable and those over 0.80 is good.

3.5.1.2            Descriptive Analysis.

This analysis functions as a medium to summarize the demographic data at the first part of the questionnaire.  The data that is measures are includes showing the frequencies and percentage for all demographic background which consists age, gender, education level, tenure of service, and working department.

3.5.1.3 Pearson Correlation Analysis.

A Pearson Correlation will analyse the strength and significant relationship of all variables that were measured and is symbolise by ‘r’ value.  Pearson’s Correlation Coefficient ( r ) is measure the strength of the relations between the two variables and it should not be calculated if the outcomes not linear.  Furthermore, if the value is more than 0 indicates that there is a positive relations between two variables. In addition, if the value indicates less than 0, it shows that there is a negative relation between two variables.

3.5.1.4            Multiple Regression Analysis.

This study used multiple regression analysis which includes one dependent variable (Communication) and two independent variables (Motivation, and Understandings).  This analysis was used to determine which factors are significant.  The relationship between the three independent variables and dependent variable can be observe when the p value is smaller than 0.01 (p < 0.01) and the value of R square was used to measure the percentage of independent variables that affect dependent variables.