Observed differences in the levels of DDT were examined using analysis of variance (ANOVA). Differences were examined with a two-factor ANOVA with the factor "station" and "period" fixed and with the factor "period" nested within "station"(10)) . Fixed factors are those which are concerned with specific identifiable treatments (eg specified areas or specified times such as months or seasons), whereas random factors are those concerned with a general problem (eg increases in a broad area with samples taken from randomly chosen locations from within that area). The construction of hypotheses which require analyses using a fixed factor model infers the adoption of a more precautionary approach(11)) . A fixed factor model will have much lower critical F values than a random factor model and is more likely to detect a significant difference.

Interactions among period and area were only investigated further if both of the main factors (Period and Station) were significant. Significant main effects were examined using the Student-Newman-Keuls (SNK) multiple comparison procedure to isolate which treatments differ from others. The approach followed here is an internationally recommended technique for use in environmental monitoring(12)) . For all of the analysis of variance techniques performed during the monitoring programme, initial analyses were performed to ensure that the data were compliant with the specific assumptions of analysis of variance. These assumptions state:

• the data within and among samples must be independent of each other;

• the variance within samples must be equal (tested through the use of the Levene's median test); and,

• the data among the samples must be normally distributed (tested through the use of the Kolgomorov-Smirnov test).

As is typical with data gathered during environmental surveys, much of the data failed to agree with the latter two assumptions. When this was the case, appropriate transformations such as the logarithmic transformation were used (for DDT Log10 transformation was used) and the data re-tested for compliance with the assumptions.

Data obtained from the ten sampling stations were analysed statistically for significant differences in sediment DDT concentrations both spatially and temporally. A complete list of the raw data is provided in Annex A. Summary information of the statistical analysis conducted and results are shown in Table 2.3b.

SNK result P < 0.05
VS3 WS1 DS3 SS3 ES2 TS2 NS4 PS6 MS15 MS5

Results of the Two-Factor ANOVA followed by the SNK multiple comparison procedure test showed that Stations VS3, WS1 and DS3 had significantly (P < 0.05) higher Total DDT concentrations than all other stations except SS3. There was a degree of overlap between stations SS3, ES2, TS2, NS4 and PS6. The lowest concentrations of DDT were reported from the two stations in Mirs Bay, MS15 and MS5. As the sample sizes were small, power analysis was conducted on the log-transformed data. Results showed that power was high (1.00) and there was no chance of committing a Type II error (failing to detect a significant difference). None of the stations showed significant temporal changes in DDT concentration (Table 2.3b).