Testing the Difference Between the Respondents Demographic Groups

Differences between demographic demographics groups of test respondents are as described in Chapter 4: Table 4-3. There is a big difference in the number of respondents in a specific population group. Likewise, the academic record group affected three high schools, 185 graduate students and 85 graduate students. Therefore, the result of promoting the test on the difference of the average values ​​of these groups may be ineffective and meaningful.

Table C - 2 shows the statistically significant difference between the type of practice (group and solo) between respondents and unresponsivers. In order to test whether this difference brings some bias, we analyzed the percentage of overall complaints of healthcare HMOs, and the differences between groups and independent physicians. The proportion of physicians who are dissatisfied with HMO varies by 10 percentage points for different types of practice. Therefore, further analysis is required. Assuming that respondents from the same type of practice as non responders have the same dissatisfaction, we calculate the percentage of overall dissatisfaction assumed for all 2,500 physicians in the sample did. In this calculation, the 42% dissatisfied rate slightly decreased (43% of respondents). This difference is not statistically significant

Since it is known that independent variables (tangible, reactive, trustworthy, guaranteed, sympathy) will properly explain the dependent variable (quality of service), it is sufficient to test only the differences between respondents and dependent variables. Select only relevant demographic variables to check. These demographic variables are age, income level and nationality. As discussed in literature review, there may be differences between respondents based on these demographic variables and their expectations and performance reviews. Because it is the most appropriate test to determine whether groups are different from each other, we will perform a one-way Anova test. Assumptions on normality of interval scaling dependent variable (overall quality of service), grouping variable of 3 or more groups, and dependent variable are satisfied

T Sightseeing and Variance Analysis (ANOVA) to explore the differences between different population recognition and attitudes on the development of dark tourism. The above four newly created variables are regarded as dependent variables, regardless of whether they are perceived or not. T-test showed that there is no difference in perception and attitude between male and female. Compared with people who moved in from outside, the residents born in this place show lower scores in the variables "cultural reconstruction and environmental protection" and "attitudes towards dark tourism", but "social obstacles" and " "Social disorders" "High aspect score, environmental deterioration" However, differences between "recovery and economic development" between the two groups were not recognized. People who have worked in tourism industry