6. KS and AD test, Pearson's correlation:
Both the KS and AD test focus on whether the data follows the Normal distribution. From the result of my analysis, we could conclude that the rent is not following the Normal distribution. Moreover, we could infer that there must be something that skewed the rent distribution. 
For the Pearson's correlation, the return values could be used to measure the level of correlation between the two features. We could see that both the noise and metro are strongly correlated to rent while the noise has a better one. 

Conclusion: 

For the series of maps shown above as well as in the notebook, we could conclude that the lower Manhattan and downtown are the two places with the highest rent, and at the same time, have most noise complains and most crimes happened. Moreover, there are strong correlation relationships found between rent and noise complaints/metro entrance distribution. 

Possible improvement: 

It is clear that this model is an oversimplified one. There must be much more than 6 factors that could influence the rent. For example, the education quality of the nearby schools, the quality of medical resource that could be obtained by the dwellers, and the area of the local green space. Moreover, the data processing is also coarse. Let's take the crime data as an example: Three different levels of severity were assigned for crime records: felony, misdemeanor, and violation; and the severity of the consequence is largely different. So that in a more mature model, people should consider assigning different weight to those three when using the criminal behavior record to measure the level of security in some area.  Also, the spatial autocorrelation is worth to spend some time to gain the whole picture of the rent analysis project. 

References:

ESRI, (n.a.). GIS Dictionary, Retrieved fromhttps://support.esri.com/en/other-resources/gis-dictionary/term/69d9b932-d1be-4558-bb0f-ebca02292b31
Manhattan Community Board 1. (2017, May). Livability Index: A comparison of the Quality of Life across NYC’s Community Districts to help Community Boards better serve their residents. Retrieved fromhttp://www1.nyc.gov/assets/manhattancb1/downloads/pdf/studies-and reports/july2017-cb1-livability-index-study.pdf
Github repos:
https://github.com/gboeing/urban-data-science/blob/master/20-Accessibility-Walkability/pandana-accessibility-demo-simple.ipynb
https://github.com/dloomer/for-rent
http://nbviewer.jupyter.org/gist/perrygeo/c426355e40037c452434
https://github.com/fedhere/PUI2018_fb55/blob/master/midterm/treesJustice_solution.ipynb