Data analysis – Community grant – k Nearest Neighbor and Naive Bayes

See attached file

Part 1

write an Executive Summary of a research proposal in your area to an audience of lay reviewers. Method to be adopted may be the k-Nearest-Neighbor data mining technique or Naive Bayes. The goal is to convince the panel that your project should be funded.

Part 2


Identify a current (open within the last year) granting opportunity in community-based research. This may be anywhere on the planet – the goal is simply to leverage the language used in the scope of projects to frame your responses in subsequent steps. Provide the title of the granting opportunity and the hyperlink. 


In ten or more sentences, write a compelling narrative explaining (1) the problem your research question will address, (2) why and how that problem is important, and (3) how findings from your work will transform the space (e.g. recidivism rates, access to healthcare, financial education, etc). one image is acceptable if properly referenced, annotated, and labeled. 


In ten or more sentences, (1) explain what k-Nearest-Neighbor analysis/Naive Bayes is, (2) how it will be used in your research, (3) the data set you will analyze, and (4) your anticipated outcomes. It is recommended that the final sentence in this section tie into what was presented in Section A.