In chapter 4 of the current research work, the coding as well as the decoding of the gathered data is provided which better helped to make use of the Version 22 of SPSS (Statistical Package for the Social Sciences). The results obtained after performing different tests on the data as well as the relevant interpretations are the part of current chapter. There are certain categories & the digits which are first defined for each of the item of the questionnaire. In this chapter, the details about the demographics, the reliability analysis, descriptive statistics, correlation coefficient and the regression analysis are also discussed. The varying scale as well as the categories which are assigned to the questionnaire items better helped to evaluate the questionnaire items.

Coding and Recording of data of payment card fraud affect the UK users

The raw data was first recorded to the excel sheet. It was then transformed the SPSS platform by copying the data from the excel sheet and pasting the same to the Version 22 of the SPSS. In order to collect the data for the current research work, the questionnaire is used. The study dependent and the independent variables are assigned different categories according to the response scale being used for the questionnaire.

 Preliminary Analysis of payment card fraud affect the UK users

In order to evaluate the data and to interpret the results, SPSS is used.  The reliability of the data set is determined by the use of Cronbach Alpha Value. As far as the descriptive statistics is concerned it is all about the mean as well as the standard deviation. The relationship of the study dependent and the independent variables is evaluated by the use of correlation coefficient. The regression analysis helped to make decisions whether to accept or reject the study hypotheses. The main aim behind conducting these tests is to determine the reliability as well as the association of the study dependent and the independent variables.

The questionnaire contains two parts as given:

·         Demographics (for current work they are treated as the control variables)

·         The independent and the dependent variables of the current study.

The particular categories and the digits are assigned to the variables first and then the data is gathered from the respondents. For the demographic variables, the assigned categories are as given:

Table 4.1: Demographics & categories

Data Reliability Analysis of payment card fraud affect the UK users

The data reliability is accessed by using the Cronbach Alpha Value for the current study variables. The idea of Cronbach Alpha was introduced in 1951 by Cronbach. The range for the Cronbach Alpha lies between 0 and 1. It shows that all the items of the questionnaire are better evaluated on the similar concept & idea. The data set for which the value of Cronbach Alpha is more than 0.70 it means that the data is highly reliable (Nunnallly, 1978). For the present research work, the overall value of the Cronbach Alpha is shown in table 4.2.

Table 4.2: Cronbach Alpha

The above table is showing that the overall Value of Cronbach Alpha is greater than 0.70 i.e., .870. It means that the data items are highly reliable.

Frequency Analysis of survey of payment card fraud affect the UK user

The responses of the respondents are better evaluated through the frequency distribution. Following is given the frequency distribution along with the respective pie-charts for the demographic variables.

Interpretation

The information related to the frequency distribution and the relevant percentages for the respondents of the age is given in the table 4.3. 27.6% of the respondents are a part of the age range 18-24 years and the frequency for the said age range is 65. 24.4% of the respondents belong to the age range of 25-34 years and the relevant frequency is 59 respondents. The respondents which belong to the age range of 35-4 years and 45 or above have the frequency of 59 and 57 respondents along with the relevant percentages of 24.4% and 23.6% respectively. Most of the respondents are the part of age range 18-24 years with 27.6%.

Interpretation of payment card fraud affect the UK users

            The varying percentages for the respondents of the age are shown with various attractive colors in the above pie-chart (Wright, 2014). The major area of the pie-chart is covered by blue color which is showing the frequency of the age range 18-24 years. At the second, third and the fourth number are the age ranges 25-34 years, 35-44 years and 45 or above which are shown in the pie-chart by the colors green, yellow and purple respectively.

Interpretation of payment card fraud affect the UK users

The details related to the frequency distribution and the relevant percentages for the respondents of the gender are given in the table 4.4. 61.2% of the respondents are a part of the gender female with the frequency 148. 38.8 % of the respondents are a part of the gender male with the frequency 92. This frequency distribution shows that most of the respondents are the female.

Interpretation of payment card fraud affect the UK users

            The varying percentages for the respondents of the gender are shown with various attractive colors in the above pie-chart. The major area of the pie-chart is covered by green color which is showing the frequency of the female gender. At the second number is the gender male which is shown in the pie-chart by the blue color.

Interpretation of payment card fraud affect the UK users

The information related to the frequency distribution for the educational level and the relevant percentages for the said respondents is given in the table 4.5. 27.6% of the respondents are a part of the bachelor’s degree and the frequency for the said educational level is 67. 19.4% of the respondents belong to the Masters degree and the relevant frequency is 47 respondents. The respondents which belong to the M-Phil and the Others educational level have the frequency of 69 and 57 respondents along with the relevant percentages of 28.5% and 23.6% respectively. Most of the respondents are the part of the educational level M-Phil with the frequency 69.

Interpretation of payment card fraud affect the UK users

            The varying percentages for the respondents of the educational level are shown with various attractive colors in the above pie-chart. The major area of the pie-chart is covered by skin color which is showing the frequency of the educational level M-Phil. At the second, third and the fourth number are the respondents from the Bachelors, Others and Masters which are shown in the pie-chart by the colors blue, purple and green respectively.

Interpretation of payment card fraud affect the UK users

The details related to the frequency distribution for the employment status and the relevant percentages for the said respondents are given in the table 4.6. 17.4% of the respondents are serving as the private officials and the frequency for the said employment status is 40. 72.3% of the respondents are the government officials and the relevant frequency is 175 respondents. The respondents which belong to the ‘others’ employment status have the frequency of 25 respondents along with the relevant percentage 10.3%. Most of the respondents are the part of the employment status as the government officials with the frequency 175.

Interpretation

            The varying percentages for the respondents of the employment status are shown with various attractive colors in the above pie-chart. The major area of the pie-chart is covered by green color which is showing the frequency of the employment status government officials. At the second and the third number are the respondents from the private sector and others which are shown in the pie-chart by the colors blue and skin respectively.

 Descriptive Statistics

Table 4.7: Mean and Standard Deviation

Descriptive Statistics

Interpretation

The data related to the mean and the standard deviation is given in the table 4.7. The mean values for all the study variables (i.e., Security issues, Lack of knowledge, Technical issues and payment card frauds) are greater than 4 (i.e., 4.4583, 4.3278, 4.4708 and 4.2500 respectively). The value 4 is if measured on the five-point likert scale it shows that the respondents are highly agreed to the statements of the questionnaire. The values .55738, .62489, .61466 and .74878 are showing the variance percentage of the study variables (i.e., Security issues, Lack of knowledge, Technical issues and payment card frauds) from the respective mean values.

Correlation Analysis

The association of the study variables can better be determined by the Pearson product moment correlation coefficient. It is developed by Karl Pearson in 1985. The test results for this coefficient lie between +1 and -1. For positive correlation, test result is +1. For no relationship, test result is 0. Negative relation between the variables is depicted by -1 (Husser, 2017). The correlation analysis and its results are shown in table 4.8.

Table 4.8: Correlation Coefficient

Interpretation

In the regression model, the value of R-Square provides the measure for the goodness-of-fit. This value tends to depict the %age variance change in the dependent variable due to the independent variables (Kleinbaum, 2010). Based on the regression analysis for the current data set, it is evaluated that the value of R is 0.7. As far as the value of R-square for the current study variables is concerned, it is 0.67. This value is determining a significant percentage change on the dependent variable (i.e., payment card frauds) due to the study independent variables (i.e., Security issues, Lack of knowledge, and Technical issues). The value of adjusted R-square provides for a comparison between the study models. This value is 0.63 which shows that out of total variation narrated by the regression line, the variation %age is not that significant. In case we talk about the value of p for the regression model, this value is less than 0.05 for all the study independent variables. The value of p<0.05 shows that the study independent variables (i.e., Security issues, Lack of knowledge, and Technical issues) are positively significantly associated with the study dependent variable (i.e., payment card frauds). It can be said that these parameters better help to determine the payment card frauds which can have the varying reasons to take place.

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