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Strategy Document

Date: Jan 24, 2024 Prepared by: Andrew C.

Introduction

This document outlines the strategy for performing the statistical and exploratory analysis of New York's Pastry/ Dessert oriented businesses. This document aims to streamline the project process and ensure quality deliverables and time management. This document was drafted after the project was completed. However, this document serves as practice for future projects to outline milestones and achievements.

Plan

Establish project scope

* Use Yelp's API to uncover hidden trends that increase the likelihood for a business's success.
* We will define success as the number of reviews and average rating above median value.

Analyze

Collect, prepare, analyze data

* API key was generated through Yelp's developer site.
* Extract, Transform and Load data into usable formats.
* Clean, tidy data for usability.

Construct

Model selections and apply machine learning algorithms

* Apply statistical methods between features of data (business types, spatial clustering)
* Use methods like Chi2, ANOVA and Tukey to observe relationship/ independence between each feature.
* Use DBSCAN clustering to observe regions of NYC with higher rates of success.

Execute

Communicate findings to stakeholders and address feedback.

* Stakeholders are investors with no knowledge of statistics and clustering algorithms.
* Address shareholder feedback.
* Draft presentation in a readable/ understandable format.
* Dashboard findings for ease of access.
* Address any limitations of analysis.