data normalization >> in order to overcome the differences between the level of citizenship engagement
Census data
API
Weaknesses of the data
Methodology: what analytical tools were used, why were they the appropriate tool? Give references here to the use of these tools in similar contexts and the strengths and weaknesses of the methods. What methods could not be used because the data was not supporting them, but would have been able to answer the question. (You probably want to include plots and tables here too).
Conclusions and Limitations:
The analysis revealed permit issuance's significantly low predicting power for building violations complaints. The initial assumption, according to which higher number of permits issued in a certain place will probably mean the same place will encounter less building violation complaints did not approved in this research. Even when dividing the data into two samples - of Manhattan and Brooklyn, there was no consistency detected in the behaviour of the variables and their relationship.
Possible limitations and/or further work could analyze DOB approved violations rather that 311 data, although being normalized.
Could be helpful to assess the residents-per-permit and by this to normalize the overall affect of each permit over the city as a whole.
What did you find? How does it compare to previous findings, how does it comare to your expectations when you strted the project and why was any question ananswered or not answered adequately by this analysis?
Future work: what improvements to the analysis, or what data would be needed to improve the result?