Global Autocorrelation

To investigate whether the data does spatially cluster, the statistical model known as Moran’s Test is performed. The output of the model is Moran I test statistic, which is number between -1 and 1 where 1 determines perfect positive spatial autocorrelation (so the data are clustered), 0 implies that the data are randomly distributed and -1 corresponds to negative spatial autocorrelation, so dissimilar values tends to be next to each other. The table below shows Moran I test statistic and corresponding p value for each variable.

From the tests‘ outputs we can conclude that there is strong positive spatial autocorrelation for Price, Metro, Train and Tram distance variables and these data spatially cluster. Regarding the Area, the p value is above 0.05, so we can conclude that there is no significant spatial clustering of the data and as the test statistic is near zero, we can conclude that the data are most likely to be randomly distributed. For the Bus distance, the p value is below 0.05 so there is significant spatial pattern in the data however, as the test statistic is 0.514, the relationship is much weaker when comparing with other distance variables. It might suggests that there is some spatial pattern for local spots but not for the entire dataset.