CHAPTER 3: RESEARCH METHODS 3.1. Introduction
3.9 Procedure of Data Analysis
Data analysis is a procedure that gathers and arranges the data before determining whether to accept or deny the hypothesis (Pickell, 2022). The data collected for this research will be computed and analysed using the Statistical Package for the Social Science (SPSS). SPSS is a multi-purpose and responsive program designed to run a wide range of statistical procedures and
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ability to analyse data using methods such the descriptive analysis, reliability test, Chi-square test, and spearman correlation analysis makes this programme useful.
3.9.1 Pilot Test
According to Formplus Blog (2022), Pilot testing includes a number of procedures that let assess the many facets of the researcher's project in advance. The researcher may also refer to this as a trial run or preparation to help identify any flaws in plan before start putting it into action. It is advisable to do pilot studies for qualitative and quantitative research (Enago Academy, 2022).
Before we conduct our major study, we can evaluate our research method with a limited sample size of test participants by doing a pilot test. By doing this, we can make sure that our user research goes well and significantly enhance the results of our study.
To further clarify, the research's required subgroups will be tested in the pilot test. In order to conduct a pilot test, 30 sets of questionnaires are indeed being given out to the intended respondents. The Statistical Package for Social Sciences (SPSS) software will be used to enter the data after it has been collected to determine its reliability. Finally, if any issues are found, the questionnaires will be disseminated for the actual research after being revised based on the findings of the pilot test.
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A descriptive analysis will be utilized to describe the characteristics of the data through mean, median, standard deviation, variance, range, and percentile. This is a technique to list the information gathered and explain the information that was present in the sample. Therefore, descriptive analysis can help researchers to study features that will influence research conclusions.
These data will then be transformed. Detailed explanation of the results will be in Chapter 4.
3.9.3 Reliability Test
According to Rosaroso (2015), reliability is a critical quality of any test whether written test, performance appraisal, informal observation or questions. Therefore, reliability is also known as consistency or repeatability of such measurements (Anne Bruton, 2000). This has to do with the accuracy of the measuring instrument. According to Peter M. Fayers (2002), a scale that can produce reproducible and consistent results is the meaning of reliability of scale. Reliability focuses on measuring on generate quantitative data in which interval and ratio data (Anne Bruton, 2000). We use a standard measure of instrument reliability, Cronbach's Alpha to measure reliability by calculating the reliability coefficient assesses the consistency of the entire scale with this reliability instrument and being the most widely used measure, Cronbach's alpha is a reliability coefficient that indicates the extent to which one group of items or variables is positively correlated with another. This reliability test is to ensure that consistent results will occur without bias and is an indicator for the reliability of the measurements and getting consistent measurements over time.
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A technique for assessing hypotheses is the Chi-square test. Determine whether the observed frequencies in one or more categories match the anticipated frequencies using two common Chi-square tests. Since there are two measurement variables between the independent and dependent variables, we employ the Chi-square test of independence. This type will decide if the two variables might be related or not related.
3.9.5 Spearman Correlation Analysis
The Spearman rank-order correlation coefficient (also known as Spearman's correlation) is a nonparametric indicator of the strength and direction of a link between two variables evaluated on at least an ordinal. The test is used on ordinal variables and continuous data that do not satisfy the requirements for the Pearson's product-moment correlation. The range of Spearman's correlation coefficients lies between -1 and +1. We may determine whether a relationship is monotonic and positive or monotonic and negative by looking at the sign of the coefficient. A positive correlation means that as one variable rises, the other tends to follow. Two variables that are negatively linked tend to move in opposite directions as one rises. Stronger links are represented by values near -1 or +1 than by values around zero.
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This methodology is inclusive of the research design that will be used in this study. The determination of the population and sample is as it has been set includes all employee in Selangor and Johor by using the distribution-free methods. To obtain more accurate information on the relationship between the post-pandemic effects on employee job performance in Malaysia (Johor and Selangor), researchers need to use primary data by distributing questionnaire to respondents who have been target. The data obtained will be collected and then analysed and discussed to obtain the desired results of the research on the relationship between the post-pandemic effects on employee job performance in Malaysia (Selangor and Johor). Methods of analysis used to conduct analysis of data of this research are SPSS, descriptive analysis, reliability test, Chi-square test, and spearman correlation analysis. All these methods will be used to analyse the data obtained which will all be discussed in more details in chapter 4.
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CHAPTER 4: DATA ANALYSIS AND FINDINGS