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denotes a signi cant variable to quantify solid waste for the waste group at the 95 percent con dence level. (Note: 12 of the 20 waste groups were described by the number of employees alone).
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Waste Group Agriculture x1 = # employees 0.83 122.06 4.23 7.14x1 3.49x2 140.4x3 + 371.10 2.18 0.86 0.79 0.84 71.48 31.50 749.43 0.84 0.80 21.10 0.43x1 0.94 3.54x1 + 11.81 0.25x1 + 35.68 0.51x1 + 6.48 0.000
Number of Companies Indicators x1 = # employees 13 Regression Model 1.29x1 0.27 t Statistic t Critical P Value Partial R 2 R2 0.79 F F Statistic Critical P Value 41.38 4.75 0.000
Adjusted R2
Automotive sales, service, and repair
Chemical and rubber manufacturers x1 = # employees x1 = # employees x1 = # employees
x1 = # employees x2 = disposal $/ton x3 = ISO14001cert. x1 = 0.51 x2 = 0.14 x3 = 0.19 3.49 3.92 4.35 5.59
x1 = 5.46 x2 = 3.02 x3 = 3.47 x1 = 0.000 x2 = 0.011 x3 = 0.005
0.000 0.000 0.000 0.000
Commercial and government
Construction
Education
Electronic manufacturers 2.26 0.78
x1 = # employees x2 = disposal $/ton x3 = ISO14001cert. x1 = 0.59 x2 = 0.04 x3 = 0.15 0.76
x1 =8.67 2.29x1 0.83x2 56.31x3 + x2 = 2.27 126.63 x3 = 4.51 x1 = 0.000 x2 = 0.033 x3 = 0.000
Food manufacturers 2.57 x1 = # employees x1 = # employees x1 = # employees 0.98x1 + 21.64 2.01x1 + 4.05 2.71x1 + 8.27
x1 = # employees x2 = disposal $/ton x3 = ISO14001cert. 0.90 0.81 0.82 0.80
x1 = 4.53 7.19x1 5.17x2 183.5x3 + x2 = 2.85 577.16 x3 = 2.89
x1 = 0.011 x2 = 0.046 x3 = 0.044
x1 = 0.50 x2 = 0.19 x3 = 0.21
12.35 29.84 22.39 47.11
5.79 5.32 5.99 4.67
0.017 0.000 0.000 0.000
Food stores
Hotels
Medical services
Metal manufacturers 2.48 x1 = # employees 5.21x1 +19.8
x1 = # employees x2 = disposal $/ton x3 = ISO14001cert.
x1 = 4.81 8.21x1 7.51x2 214.93x3 + x2 = 3.08 756.46 x3 = 2.52 x1 = 0.003 x2 = 0.022 x3 = 0.045
x1 = 0.60 x2 = 0.20 x3 = 0.10
0.90 0.85
18.86 17.00
4.76 7.71
0.002 0.001
Mining
Paper manufacturers and printers x1 = # employees x1 = # employees 5.91x1 + 19.87 0.78x1 +2.27 x1 = # employees 1.87x1 0.41
x1 = # employees x2 = disposal $/ton x3 = ISO14001cert. x1 = 4.83 6.63x1 3.51x2 114.82x3 + x2 = 2.65 340.27 x3 = 2.48 2.23
x1 = 0.001 x2 = 0.024 x3 = 0.033
x1 = 0.58 x2 = 0.15 x3 = 0.10
0.83 0.78 0.83 0.81
16.35 42.55 53.71 2173.42
3.71 4.67 4.75 4.04
0.000 0.000 0.000 0.000
Recreation and museums
Restaurants
Retail and wholesale
Textile and fabric manufacturers
x1 = # employees x2 = disposal $/ton x3 = ISO14001cert.
x1 = 5.88 7.29x1 3.78x2 92.36x3 + x2 = 3.38 40.5 x3 = 2.36
x1 = 0.000 x2 = 0.008 x3 = 0.042
x1 = 0.56 x2 = 0.20 x3 = 0.09
Transportation equipment manufacturers
x1 = # employees x2 = disposal $/ton x3 = ISO14001cert.
x1 = 5.06 2.97x1 1.73x2 56.22x3 + x2 = 2.54 412.84 x3 = 2.36
x1 = 0.000 x2 = 0.029 x3 = 0.040
x1 = 0.58 x2 = 0.11 x3 = 0.10
Wood and lumber manufacturers
x1 = # employees x2 = disposal $/ton 17.40x1 7.76x2 217.59x3 + 473.93 x3 = ISO14001cert.
x1 = 6.99 x2 = 3.73 x3 = 2.99
x1 = 0.000 x2 = 0.004 x3 = 0.014
x1 = 0.65 x2 = 0.15 x3 = 0.08
Figure 16.5 quantities).
Stepwise regression results for the 20 waste groups (signi cant variables that in uence solid waste
SOLID WASTE ESTIMATION AND PREDICTION
1.00 0.90 0.80 0.70 0.60 R2 0.50 0.40 0.30 0.20 0.10 0.00 AUT HTL RTL FDS MED CON ARG REC WDM MLM ELM PPM TRM FBM CHM FDM GOV MIN EDU RST
20 Waste groups
Figure 16.6 Coef cient of determination (R 2) analysis for the variable: number of employees.
in uential in predicting annual solid waste at the 95 percent con dence level and the full stepwise regression results for each of the 20 waste groups. The remainder of this chapter discusses the regression results from the previous table and compares the 20 waste groups to gain insights on waste generation in the United States. As shown in the preceding table, 50 to 85 percent of the total variation (R2) in annual waste generation is attributed to the number of employees for each waste group. The chart in Fig. 16.6 provides a visual comparison. The chart in Fig. 16.7 provides a comparison of the total and partial coef cient of determination for each of the 20 waste groups. This chart indicates that 79 percent to 90 percent of the variation in annual solid waste generation was accounted for by the three signi cant independent variables identi ed for the 20 waste groups (at the 95 percent con dence level). The magnitudes of the regression coef cients were compared for each of the 20 waste groups. The charts in Figs. 16.8 through 16.10 display this comparison. The previous procedure determined the signi cant variables that in uence annual solid waste quantities for each group. The next step involved interpreting the results, identifying trends, and creating new knowledge. Two categories of analyses were conducted (from the regression analyses):
Analysis of the variables that entered the prediction equations Analysis of the variables that did not enter the prediction equations
First, the variables that did enter the regression equation were examined. Standardized regression equations were established to equally compare the stepwise results. This was accomplished by forcing the constant terms in each regression equation to zero. This was completed using SYSTAT software. Tables 16.4 to 16.6 display the standardized regression coef cients for each waste group.
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