While the descriptive analysis of the results is particularly useful to visualize participants’ responses and to interpret the results, it is crucial to use inferential statistics to draw conclusions from the data [457], [1], [458]. Thus, various statistical tests suitable to the different types of variables used have been performed to determine associations and correlations between the responses (see Appendix J).
5.1.2.1. Demographics
Concerning demographics, association between gender and saving water to help the environment was tested using the chi-square test for homogeneity (see Table 5-3)[486], [487]. The null hypothesis states that the difference between the population proportions in female and male participants saving water to help the environment is equal to 0. Two samples of 100 males and 100 females were randomly selected. 62 female participants stated saving water to help the environment compared to 55 male participants, a difference in proportions of 0.07. However, there was no statistically significant difference between the two independent binomial proportions (p=0.315) and Cramer’s V (0.071) suggested a small effect size [472]. Therefore, we
84.9% 52.8%
10.6% 39.2%
0 10 20 30 40 50 60 70 80 90 100
Do you know how much you pay for your water use? Do you think that you would be more careful of your water consumption if you were aware of its costs?
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cannot reject the null hypothesis stating that the difference between the population proportions in female and male participants is equal to 0.
A binomial logistic regression was performed to ascertain the effects of age on the likelihood that participants save water to help the environment (see Table 5-2) [488], [489]. There was no studentized residual. The logistic regression model was not statistically significant, χ2(1) = 0.002,
p=0.968. The model explained 0% (Nagelkerke R2) of the variance on the likelihood that
participants save water to help the environment and correctly classified 61.6% of cases. Sensitivity was 100%, specificity was null, positive predictive value was 61.6% and negative predictive value was null. Yet, the Hosmer and Lemeshow test indicated that the model was not a poor fit (p = 0.550). Age as a predictor variable was not statistically significant, p= .968. However, the odds ratio Exp(B) = .997, 95% CI = 0.883 to 1.12 suggests that the odds of saving water to save the environment slightly decreases as age increases [460]. However, paradoxically, the odds ratio of considering water as an important issue in age 35 to 54 versus age 16 to 34 is 1.099 (95% CI = 0.858 to 1.408), 1 in age 35 to 54 versus 55 and over (95% CI = 0.2 to 50.397), 1.025 in age 55 and over versus 16 to 34 (95% CI = 0.802 to 1.311). This shows that individuals are more likely to consider water conservation as an important issue as age increases.
To further this analysis, the Cochran-Armitage test of trend, designed to test association between an ordinal independent variable and a dichotomous dependent variable, was then used to determine whether there was a linear trend between age and the wish to save water to help the environment (see Table 5-3) [490], [491]. The null hypothesis tested was ‘HO: There is no linear
trend in binomial proportions across age categories’. The age categories included were 16-34 (n=363), 35-54 (n=925), over 55 (n=961), and the proportions of respondents who reported saving water to help the environment was 0.595, 0.619, 0.601, respectively. The Cochran- Armitage test of trend did not show a statistically significant linear trend between age and saving water to help the environment. p = .805. Therefore, we cannot reject the null hypothesis and cannot accept the alternative hypothesis.
A binomial logistic regression was performed to ascertain the effects of age on the likelihood that participants save water to reduce bills (see Table 5-2) [488], [489]. There was no studentized residual. The logistic regression model was not statistically significant, χ2(1) = 0.233, p = 0.629.
The model explained 0% (Nagelkerke R2) of the variance on the likelihood that participants save
water to help the environment and correctly classified 55.2% of cases. Sensitivity was 100%, specificity was null, positive predictive value was 55.2% and negative predictive value was null.
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Here again, the Hosmer and Lemeshow test however indicates that the model was not a poor fit (p = 0.732). Age as a predictor variable was not statistically significant, p= 0.629 but the odds ratio Exp(B) = 0.972, 95% CI= 0.867 to 1.09 suggests that the odds of saving water to reduce bills slightly decreases as age increases [460].
Table 5-2. Binary regression analysis results regarding the effects of age on the likelihood that participants save water to help the environment.
B S.E Wald df p Odds
Ratio 95% CI for Odds Ratio Lower Upper Saving water to help the environment
Age -0.003 0.062 0.002 1 0.968 0.997 0.883 1.127
Saving water to reduce bills
Age -0.028 0.059 0.233 1 0.629 0.972 0.867 1.090
To determine whether the type of housing tenure was associated with the willingness to buy and install water saving devices, a chi-square test for homogeneity was performed with the null hypothesis ‘HO: the difference between the population proportions in individuals who own and
individuals who rent is equal to 0’ (see Table 5-3)[486], [487]. Two random samples of 198 participants were selected among individuals who own (group 1) and individuals who rent their property (group 2) included those who rent. In Group 1, 52.1% of the respondents reported that they would invest and install water saving devices, compared to 47.9% in Group 2, a non- statistically significant difference in proportions of .05, p= .584. Cramer’s V (0.04) also suggested a small effect size [472]. Therefore, we fail to reject the null hypothesis. However, based on the odds ratio, the odds of investing in water saving devices are 1.17 times higher if individuals own their properties than if they rent [460].
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Table 5-3. Summary of the statistical analysis for the ‘demographics’ variables (Ask Cardiff).
Variables Test Sig. Diff. Proportions
Age/Saving water to help the
environment Cochran-Armitage 0.805 N/A
Gender/ Saving water to help the
environment Chi-square for homogeneity 0.315 0.07 Type of property (owned or
rented)/Willingness to buy and install water saving devices
Chi-square for homogeneity 0.584 N/A
5.1.2.2. Awareness of Water Usage and Attitudes Towards Water Conservation To determine whether being aware of the amount used was associated to the feeling of doing enough to save water, a chi-square test of independence was conducted (see Table 5-4) [487], [492]. All expected cell frequencies were greater than five. There was a statistically significant association between the awareness of water used and the feeling of doing enough to save water χ2(4) = 189.045, p<0.0005. Cramer's V (.203) suggested a large effect size [472].
Therefore, we can reject the null hypothesis ‘H0: ‘Awareness of water used’ and ‘feeling of
currently doing enough to save water’ are independent’ and accept the alternative hypothesis. Similarly, a point-biserial correlation was run between the number of water saving devices owned by respondents and the feeling of currently doing enough to save water (see Table 5-4)
[493]–[495]. Random samples of 50 participants for each group were selected. Group 1 refers to individuals who think they currently do enough to save water and Group 2 refers to those who think they currently do not do enough to save water. Data are mean ± standard deviation, unless otherwise stated. Preliminary analysis showed that there were (a) no outliers in the data, as assessed by inspection of a boxplot for values greater than 1.5 box-lengths from the edge of the box, (b) the number of devices was normally distributed for both Group 1 and Group 2, as assessed by visual inspection of Normal Q-Q Plots and (c) there was homogeneity of variances for the number of water saving devices owned for Group 1 and Group 2, as assessed by Levene's test for equality of variances (p = .858). There was a statistically significant correlation between the feeling of doing enough to save water and the number of devices owned, rpb(98) = 0.247, p= 0.013,
with Group 1 owning more devices than Group 2 (1.2 ± 0.94 versus 0.7 ± 0.86). The feeling of currently doing enough to save water accounted for 6.1% of the variability in the number of devices owned and Cohen’s d = 0.55 suggested a moderate effect size [472], [476].
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To test whether individuals who save water for environmental reasons are more inclined to buy and install water saving devices than people who do not save water for such reasons, a chi-square test for homogeneity was performed (see Table 5-4) [486], [487]. Random samples of 50 participants who ‘are motivated to save water to help the environment’ and of 50 participants who ‘are not motivated to save water to help the environment’ were selected. Out of the 50 respondents who save water for environmental reasons, 16 (32%) would be willing to buy and install water-saving devices compared to 7 (14%) respondents among those who do not save water for environmental reasons, a statistically significant difference in proportions of 0.09, p=0.032. Cramer’s V also suggested a small to moderate effect size (0.214) [472]. Therefore, we can reject the null hypothesis that states that the difference in proportions between the two groups in the population is 0 (zero) and accept the alternative hypothesis and affirm that the two proportions are not equal in the population.
Table 5-4. Summary of the statistical analysis for the ‘awareness of water usage’ variables.
Variables Test Sig. df Cramer’s
V Variability/
Diff.
Proportions
Being aware of amount of water used/Feeling of currently doing enough to save water
Chi-square test of
independence <.0005 4 0.203 N/A
Number of water saving devices owned/Feeling of currently doing enough to save water
Point-biserial
correlation 0.013 N/A N/A 6.1%
Saving water to help
environment/Willingness to buy and install water saving devices
Chi-square test
for homogeneity 0.032 1 0.214 0.09
5.1.2.3. Financial Concerns
To understand whether knowing the price paid for water was associated with individuals’ motivation to save water to reduce their bills, a chi-square test for association was conducted between these two variables (see Table 5-5). All expected cell frequencies were greater than five. There was a statistically significant association between the motivation to save water to reduce bills and knowing the price paid for water, χ2(1) = 14.855, p < 0.0005. However, the association
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Table 5-5. Summary of the statistical analysis for the ‘financial concerns’ variables.
Variables Test Sig. df Cramer’s
V/Phi
Saving save water to reduce bills/Knowing the price paid for water
Chi-square test for association < .0005 1 0.081
A binomial logistic regression was performed to ascertain the effects of being motivated to save water to reduce bills on the likelihood that participants invest and install water-saving devices (see Table 5-6) [488]. The logistic regression model was statistically significant, χ2(2) = 35.082, p
< .0005. The Hosmer and Lemeshow test indicated that the model is not a poor fit (p = 0.772). The model explained 2.0% (Nagelkerke R2) of the variance in the willingness to invest and install
devices and correctly classified 68.6% of cases. Sensitivity was 100%, specificity was null, positive predictive value was 68.6% and negative predictive value was null. The motivation to save water to save bills, as a predictor variable of investing in water-saving devices, was statistically significant (p<0.005) (see Table 5-6). The odds ratio Exp(B) = 1.727, 95% CI = 1.437 to 2.076 suggests that individuals who save water to reduce their bills have 1.72 times higher odds to be willing to buy and install water saving devices.
In line with this, a binomial logistic regression was performed to ascertain the effects of knowing the price paid for water bills on the likelihood that participants invest and install water-saving devices (see Table 5-6)[488]. The logistic regression model was statistically significant, χ2(1) =
0.450, p=0.502. The model explained 0% (Nagelkerke R2) of the variance in the willingness to
invest and install devices and correctly classified 68.6% of cases. Sensitivity was null, specificity was 100%, positive predictive value was 68.8% and negative predictive value was null. knowing the price paid for water bills as a predictor variable was not statistically significant (see Table 5- 6). The Hosmer and Lemeshow test indicated that the model was a poor fit (p = 0.772). However, the odds ratio Exp(B) = .918, 95% CI = 0.715 to 1.179 suggests that individuals who know the price of their bills are slightly less likely to be willing to buy and install water-saving devices.
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Table 5-6. Summary of the binary regression analysis for ‘financial concerns’.
B S.E Wald df p Odds
Ratio
95% CI for Odds Ratio Lower Upper Willingness to invest and install water saving devices
Saving save water to reduce bills
.547 .094 33.951 1 .000 1.727 1.437 2.076
Knowing the price paid for water
-.85 .128 .447 1 .504 .918 .715 1.179
The Ask Cardiff survey (see Appendix A) gave insights regarding the practices, awareness and attitudes towards water conservation of a sample of Cardiff inhabitants. The results show that individuals are willing to save water, mostly to help the environment. It appeared that saving water to help the environment or to reduce the bills slightly increases the likelihood of investing in water-savings appliances. Yet, most of the respondents are reluctant to buy such devices and a large majority of them do not have any currently installed within their household. Most respondents also feel that they are currently doing enough to save water. This feeling is correlated with the number of water-saving appliances owned. Since the ‘Ask Cardiff’ survey reaches a large sample of individuals each year, it appeared useful to use this survey as a way to recruit participants for the more detailed WISDOM survey. Therefore, following a self-selection sampling method described in Chapter 4, respondents were asked if they wanted to be consulted again in the context of the WISDOM project, after completing the survey. Those who agreed were sent the WISDOM questionnaire (see Appendix B).