The strength of the relationship between the number of IBTs used in a building and the percentage BREEAM / LEED score obtained by the building can be summarised by the coefficient R . According to Cohen ( 1988 ) magnitudes 0.10 , 0.30 and 0.50 correspond roughly to relations that are considered small , medium and large respectively . An R value ( Pearson Correlation ) of 0.759 ( Table 2 ) and 0.748 ( Table 3 ) signals a very strong correlation between the variables , one that is highly significant . The fact that the sign of R is positive indicates that as the number of IBTs used in a building increases , the value of the BREEAM and LEED score increases as well . The R2 value is a standardised coefficient , which ranges from 0 to 1 ; 1 indicates a perfect fit of the data points to a straight line and 0 indicates the worst possible fit . An R2 value of 0.576 ( Table 2 ) and 0.559 ( Table 3 ) suggests a high number of data points that fit the trend line .
Table 2 : Model Summary BREEAM Case Studies ( refer to Figure 4 )
Model R Value R2 Value Adjusted R2 Value Std . Error of the Estimate
1 . 759a . 576 . 562 8.51692
Table 3 : Model Summary LEED Case Studies ( refer to Figure 5 )
Model R Value R2 Value Adjusted R2 Value Std . Error of the Estimate
1 . 748a . 559 . 497 12.06162
Additionally an ANOVA test of significance was carried out to show whether the R2 value for the relation between the two variables is significant . Since in this case the value of Significance is 0.000 ( Table 4 ) and 0.020 ( Table 5 ), which is less than 0.05 , the relation between the two variables is significantly different than zero , meaning the R2 value is highly significant .
Table 4 : ANOVA Test of Statistical Significance ( BREEAM ) ( refer to Figure 4 ) |
Model |
|
Sum of Squares |
df |
Mean Square |
F |
Sig . |
1 |
Regression |
2861.747 |
1 |
2861.747 |
39.452 |
. 000b |
|
Residual |
2103.600 |
29 |
72.538 |
|
|
|
Total |
4965.347 |
30 |
|
|
|
Table 5 : ANOVA Test of Statistical Significance ( LEED ) ( refer to Figure 5 ) |
Model |
|
Sum of Squares |
df |
Mean Square |
F |
Sig . |
1 |
Regression |
1293.211 |
1 |
1293.211 |
8.889 |
. 020b |
|
Residual |
1018.378 |
7 |
145.483 |
|
|
|
Total |
2311.589 |
8 |
|
|
|
a . Predictors : ( Constant ), No . of Intelligent Building Technologies b . Dependent Variable : Percentage BREEAM Score
3.3 Overview After the analysis it was observed that the number of IBTs in a building positively affects its sustainability rating . Some related findings about the impact different type of IBTs have on the BREEAM / LEED Scores are as follows :
• Highly integrated and interactive IBTs such as building management , energy management and facility management systems were predominantly found in buildings with a high Sustainability Rating ( EXCELLENT , OUTSTANDING , GOLD and PLATINUM ).
• Case studies with BMS and integrated systems , which shared data and interacted with other
326 ZEMCH 2015 | International Conference | Bari - Lecce , Italy