1. The problem involves interpreting and analyzing survey data presented in tables about respondents' educational background, sex, years of working experience, and position in a bank. 2. From Table 4.1, all 20 respondents (100%) have tertiary education, meaning everyone attended a tertiary institution before employment. 3. Table 4.2 shows the sex distribution: 12 males (60%) and 8 females (40%) out of 20 respondents. 4. Table 4.3 details years of working experience: 4 respondents (20%) have 1–5 years, 11 (55%) have 6–10 years, 3 (15%) have 11–15 years, and 2 (10%) have 16 years or more. 5. Table 4.4 shows positions: 8 senior staff (40%) and 12 junior staff (60%). 6. The data presentation summarizes that the introduction of e-payment systems has reduced queues and time spent in the banking hall, based on responses categorized as Strongly Agree (SA), Agree (A), Undecided (UD), Disagree (D), and Strongly Disagree (SD). 7. To analyze the impact of e-payment systems, one would typically calculate the frequency and percentage of each response category and interpret the majority opinion. 8. Since no numerical data for Table 4.5 responses is provided, a statistical test cannot be performed here. Final interpretation: The data shows a well-educated workforce with majority male and junior staff, mostly with 6–10 years experience, and a positive perception of e-payment systems reducing queue times.