3. Data analysis
A regression method was applied to explain the relationship
between a response variable and one or more predictor variables.
The respondents selected were asked their activity to sort the HSW,
to create unique handcrafted goods, and to compost HSW. The
activities of respondents in sorting HSW; creating unique handcrafted goods, and composting were given the value of “1”, while
their activities in not sorting HSW, creating handcrafted goods, and
composting were given the value of “0”. Furthermore, data from
the questionnaires were compiled and processed by binary logistic
regression.
Data were processed by determining predictor variables such
as socio-economic factors; and supporting factors. The predictor
variables were the following:
(1) The socio-economic characteristics included
(a) Gender (X1) had two categorical variables, where X1 = 1, if the
respondent was male, and X1 = 2, if the respondent was female.
(b) Age (X2) had four categorical variables, where X2 = 1, if the
respondent’s age was less than 35 years old, X2 = 2, if the respon