Page 296 - Solid Waste Analysis and Minimization a Systems Approach

274 SOLID WASTE ESTIMATION AND PREDICTION

16.4 Analysis of Results and

Summary of Findings

This section discusses the results and findings from the regression analysis conducted
on the 20 waste groups. Included in this discussion are lists of the independent vari-
ables that are significant in predicting annual solid waste for each group, the full
2
regression results (F-test, t-test, and R -coefficient of determination), ANOVA, and
correlation analysis. Table 16.3 and Fig. 16.5 display the significant variables that are

TABLE 16.3 SIGNIFICANT VARIABLES THAT INFLUENCE SOLID WASTE FOR THE
20 WASTE GROUPS

LANDFILL
NUMBER OF DISPOSAL ISO 14001
NO. WASTE GROUP NAME ABB. EMPLOYEES COST ($/TON) (YES/NO)

1 Wood and lumber manufacturers WDM × × ×

2 Metal manufacturers MLM × × ×
3 Food manufacturers FDM × × ×

4 Chemical and rubber manufacturers CHM × × ×
5 Paper manufacturers and publishers PPM × × ×

6 Transportation equipment manufacturers TRM × × ×
7 Textile and fabric manufacturers FBM × × ×

8 Electronic manufacturers ELM × × ×
9 Restaurants RST × NA NA

10 Mining MIN × NA NA
11 Food stores FDS × NA NA

12 Medical services MED × NA NA
13 Hotels HTL × NA NA

14 Construction CON × NA NA
15 Education EDU × NA NA

16 Recreation and museums REC × NA NA
17 Retail and wholesale stores RTL × NA NA

18 Automotive sales, service, and repair AUT × NA NA
19 Agriculture ARG × NA NA

20 Commercial and government GOV × NA NA

× denotes a significant variable to quantify solid waste for the waste group at the 95 percent confidence level.
(Note: 12 of the 20 waste groups were described by the number of employees alone).