Statsquatch: A Data Expedition into Bigfoot Sightings

STA/ISS 313 - Spring 2023 - Project 1

The Tibbles: Anik Sen, Aryaman Babber, Matt Mohn, Nhu Bui

Introduction

‘Bigfoot’ TidyTuesday Dataset

• Creator: Timothy Renner, Data World 2017

• Data Source: Bigfoot Field Researchers Organization (BFRO), Dark Sky API

• Dimensions: 5,021 rows (different Bigfoot sightings), 28 columns (details of sightings)

Non-Weather Variables (12)

observed, location_details, county, state, season, title, latitude, longitude, date, number, classification, geohash

Weather Variables (16)

temperature_high, temperature_mid, temperature_low, dew_point, humidity, cloud_cover, moon_phase, precip_intensity, precip_probability, precip_type, pressure, summary, uv_index, visibility, wind_bearing, wind_speed

Question 1: How does the geographic distribution of Bigfoot sightings change over time?

Mainland USA Bigfoot Sightings: Pre-1970

Mainland USA Bigfoot Sightings: 1970s

Mainland USA Bigfoot Sightings: 1980s

Mainland USA Bigfoot Sightings: 1990s

Mainland USA Bigfoot Sightings: 2000s

Mainland USA Bigfoot Sightings: Post-2010

Barplot: Total Distribution

Question 2: How are precipitation conditions associated with Bigfoot sightings?

Boxplot: Precipitation Probability

Probability of Precipitation = (Confidence in Precip) x (Area of Precip)

Barplot: Precipitation Type

The End

Source: Roger Patterson and Bob Gimlin, California 1967

HAPPY HUNTING!