Thank You for Smoking

A Capstone

Eric Dolan

Background

This is a study of popularly on smoking business by looking into the number of reviews(talking points) on yelp data set challenge and understand the economic impact and very real economic trade-offs we should consider when voting on a smoking ban.

The yelp data can be find on

yelp_dataset_challenge_academic_dataset.zip

More on Yelp Dataset Challenge and the details of the data structure can be found on

http://www.yelp.com/dataset_challenge

Background

From the data set provide by Yelp, there are:

a total of 61164 businesses
only 2754 of businesses that are with the attribute smoking(both allowing indoor and outdoor)
a total of 1569264 reviews and from the period of Oct 2004 to Jan 2015
only 144080 reviews for the 2754 smoking businesses.

It is surprisingly high for only 2754 businesses.

Exploratory analysis

After understanding the data, I converted the data into a Time Series Object

only 2006 to 2014 data are use because they consist of full year data. The final transformed data will look like in fig.1

##  Time-Series [1:108] from 2006 to 2015: 88 35 23 43 27 31 44 63 73 98 ...

fig.1 - Final transformed data

Next, we move on to build a Seasonal Decomposition of Time Series by Loess model

Modelling

After a few round of tuning and experiment with different settings. We are able to produce a final model for forcasting.

plot of chunk unnamed-chunk-2

fig.2 - Final model plot

Forecast

The 2 years forecast result in fig.3, show that it remain in same zone as of today. This somehow mean there is an economic impact.

## Warning: package 'forecast' was built under R version 3.1.3

## Loading required package: zoo
## 
## Attaching package: 'zoo'
## 
## The following objects are masked from 'package:base':
## 
##     as.Date, as.Date.numeric
## 
## Loading required package: timeDate

## Warning: package 'timeDate' was built under R version 3.1.2

## This is forecast 6.1

plot of chunk unnamed-chunk-3

fig.3 - Forecast result