Consumption Decrease Comparison between Participants and Non-

As previously mentioned in the Methodology chapter, analysis was conducted in two phases. In the first phase, data were grouped in three different location groups so that the programme’s effectiveness can be evaluated for each region separately. In the second phase, all households were analysed together so that the water efficiency programme as a whole could be evaluated. Since independent samples T-test is not suitable for non- normal datasets, normality tests were conducted before the analysis.

RESULTS FOR HOUSEHOLDS IN BEDFORD, WELLINGBOROUGH, MILTON KEYNES AND NORTHAMPTON

After outliers’ removal, the remaining set of households for each of these areas was small. But due to their proximity, these areas experienced almost the same weather conditions. This allowed for them to be grouped together to form a sample of 17 participating households and 37 not-participating ones. The sample still remained small, thus normality tests were conducted so that the choice between utilising an independent samples T-test or non-parametric tests could be made.

The distributions of both samples approach the normal distribution based on the frequency graphs (Figure A1 & A2). Moreover, both the Kolmogorov-Smirnov and the Shapiro-Wilk normality tests appear to be insignificant, pointing out that we can assume a normal distribution (Field et al., 2012). Both graphs and normality tests can be found in the Appendix. Thus, the independent samples T-test is sufficient to explore whether consumption decrease between the two samples after the launch of the water efficiency programme was significantly different. The first table (A1-Appendix) presents that water consumption for the participants group shows a decrease of 17% on average whereas for the non-participants it shows on average, an increase of 3%. It should be noted that the confidence intervals for the mean do not overlap for the two groups, implying that they might not be from the same population. The second table of the output contains the main test statistics. The Levene’s test is not significant (p>.05) thus we can assume that the variances are roughly equal. The significance value of t is less than 0.05 thus we can conclude that there is significant difference between the means of the two samples. The

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Figure 4.12 Consumption decrease comparison between participants (n=17) and non- participants(n=37) in Bedford, Wellingborough, Milton Keynes and Northampton

confidence interval for the difference between means cannot be zero or negative, confirming the conclusion that consumption decrease for the participants group is significantly different than for the non-participants.

RESULTS FOR HOUSEHOLDS IN COLCHESTER AND IPSWICH

After outliers’ removal, the remaining set of households for each of these areas was small. But due to their proximity, these areas experienced almost the same weather conditions. This allowed for them to be grouped together to form a sample of 17 participating households and 37 not-participating ones. The sample still remained small, thus normality tests were conducted so that the choice between running an independent samples T-test or non-parametric tests could be made.

The distribution of consumption decrease for participants does not approach a normal distribution sufficiently, whereas for the non-participants sample, the distribution is fairly normal (see Appendix). For this reason, non-parametric tests were employed (Table A2- Appendix) to examine whether consumption decrease after the programme launch

104 differed significantly between the two groups.

It was hypothesised that consumption decrease between the two groups was the same. Based on the results from the Mann-Whitney test, consumption decrease in the participants group differs significantly from non-participants group, U=171, z=-2.67,

p<0.05.

The Kolmogorov-Smirnov test concluded in the same results. These findings confirm that consumption decrease for the participants group for the selected time period was significantly different than the consumption decrease for the non-participants group. This result suggests that water saving devices that were installed in the participating households may be the reason for this difference.

RESULTS FOR HOUSEHOLDS IN GRIMSBY

After removal of outliers, the dataset was reduced to 8 participant homes and 19 non- participants homes. The sample was small, thus normality tests were conducted so that the choice between running an independent samples T-test or non-parametric tests could be made.

Figure 4.13 Consumption decrease comparison between participants (n=17) and non- participants (n=37) in Colchester-Ipswich area

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The distribution of consumption decrease for the participants approaches a normal distribution sufficiently, whereas for the non-participants sample, the distribution is not normal (see Appendix). For this reason, non-parametric tests were employed to examine whether consumption decrease after the programme launch differed significantly between the two groups. It was hypothesised that consumption decrease between the two groups was the same. Based on the results from the Mann-Whitney test (Table A3-Appendix), consumption decrease in the participants group does not differ significantly from non- participants group, U=42, z=-1.8, p=0.075>0.05.

The Kolmogorov-Smirnov test concluded in the same results. These findings do not confirm that consumption decrease for the participants group for the selected time period was significantly different than the consumption decrease for the non-participants group. This result suggests that water saving devices that were installed in the participating households of the area may have not been successful in reducing household water consumption.

Figure 4.14 Consumption decrease comparison between participants (n=8) and non- participants (n=19) in Grimsby area

106 RESULTS FOR ALL AREAS

After removal of outliers and zero consumption records, the dataset for this analysis was reduced to 42 participant homes and 92 non-participants homes. The sample was small, thus normality tests were conducted so that the choice between running an independent samples T-test or non-parametric tests could be made. For the participants’ sample, the two tests do not agree. However, the Shapiro Wilk test is more appropriate for samples of under 50 entities, thus we can conclude that the participants sample does not follow a normal distribution since the Shapiro Wilk test was significant (p<0.05). The non- participants sample on the other hand showed important signs of normality based on both test and on the distribution graph. Since not both samples appear to be normally distributed (see Appendix), non-parametric tests were employed to examine whether consumption decrease after the programme launch differed significantly between the two groups. It was hypothesised that consumption decrease between the two groups was the same.

Figure 4.15 Consumption decrease comparison between participants (n=42) and non- participants (n=92)

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decrease in the participants group differs significantly from non-participants group, U=658, z=-5, p<0.001. The Kolmogorov-Smirnov test concluded in the same results. These findings confirm that consumption decrease for the participants group for the selected time period was significantly different than the consumption decrease for the non-participants group. This result suggests that water saving devices that were installed in the participating households may be the reason for this difference.

CONSUMPTION DECREASE BY ACORN CLASS

It would be informative to observe how the consumption of participants of different ACORN classes responded to the water efficiency devices installation. Therefore, the following chart was produced. With the exception of ACORN class 5 which was under- represented in the sample, it is evident that higher classes showed larger consumption decreases (Figure 4.16). ACORN class 1 showed the smallest decrease of all. This can be attributed to the fact that properties that belong to the first class are usually much bigger than the rest and thus have more water fixtures. Since water conserving devices were fitted only to some of the houses’ fixtures, some water using features remained as they were before. Conversely, smaller households such as those of class 3 or 4 that may have fewer water using features appear to have benefited more from the devices installation.

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CONSUMPTION DECREASE BY NUMBER OF RESIDENTS

Figure 4.17 Average consumption decrease by number of residents (n=42)

Households of 3 or more residents appear to have reduced their consumption less than households of a single or 2 residents (Figure 4.17). This can be attributed to the fact that households where more than 2 people live in are usually bigger than the ones where a single or 2 persons live. Another possible explanation for this finding is that in one- person households, the one-to-one engagement with the plumber who made the home visit may had a big impact in encouraging behavioural change. This behavioural aspect of the home visit quite possibly loses impact as the messages are shared less and less in larger household sizes. As mentioned previously, it appears that the installation of water saving devices/appliances is more effective in reducing consumption in smaller properties rather than in bigger ones. Leakage can also be a reason for this. In larger homes, leaks are more frequent since there are more appliances and pipe fittings where leaks can occur.

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4.4.3 Consumption Comparison for Participants and Non-Participants Before and