Visualizing and Forecasting Box-Office Revenues: A Case Study of the James Bond Movie Series

Vahan Petrosyan, Utah State University

This work made publicly available electronically on 26 August 2014


This Master's report deals with the visualization and forecasting of the box-office revenues and some related variables from the James Bond movie series. Visualization techniques such as time series plots, scatterplot matrices, dotplots, boxplots, histograms, normal quantile plots, parallel coordinates plots, heatmaps, mosaic plots, association plots, and choropleth maps are used to provide some deeper insights into the given dataset. Additionally, the results from an article published in 1997 are reproduced and extended.This article modeled the box-office revenues of the James Bond movie series. Numerous statistical models were examined to obtain the models that are closest to the original models. Then, these reproduced models are compared with newer methods such as LASSO and random forests to determine how to best forecast the box-office revenues of recent (and future) James Bond movies.