I am doing spatial analysis using huge national population data set. I have faced several challenges when I do the analysis. I have a point feature data with associated values. Each point feature has an average of 20 individuals with 'Yes' or 'No' option for use of family planning service. The 'Yes' option is given a value of 1 and the 'No' option to zero. The data has 622 point features and a total of 12,440 values; that is, each feature has an average of 20 values.
How can I analyse patterns and map the clusters – hot spot analysis? I started analysing the Global Statistics, using the default; however, I am getting errors messages; it ends up with zero results (Z-score, P-value, Index). I did the local statistics straightaway, I am still getting error messages. I also use the Optimized Hot Spot Analysis and it returned with errors.
I was wondering your support in this regard.
Maybe you can summarize (Summary Statistics tool? or just SUM the ones?) the number of Yes values for each of your 622 points. Then you can run Hot Spot Analysis or Optimized Hot Spot Analysis on the point counts. This answers the question: where are yes answers clustered spatially. I think another option would be to create separate points for every yes answer (so you would have coincident points at the same location only for yes answers). Then you could run optimized hot spot analysis on the point incident data. This will also show you where yes answers cluster spatially and if the clustering is statistically significant. I hope this is helpful and that other people will also have good ideas for you to try.