Cockeyed.com

How much is Inside?
Pranks!
Community & Citizenship
Height Weight Chart
Science Club
Incredible Stuff
How To Guides
Travel

About
Contact

Disaster Casualties Visualization Tool: Mountain Meadows massacre: 1857

120 Dead Men and Women

The Mountain Meadows massacre was a series of attacks on an emigrant wagon train by Mormons in southern Utah, 1857.

This was a person. He was working  his  way through all of the shows on Netflix. This was a person. He overtipped. This was a person. She always had gum. This was a person. She didn't have a family. This was a person. He snored. He loved nachos. This was a person. She had a sexy phone voice. She was convinced he was color blind. This was a person. He couldn't grow a mustache. This was a person. He taught guitar. He never ate breakfast. This was a person. He had a baby boy. This was a person. He didn't get along with animals. This was a person. She just had the bandages removed from  plastic surgery. This was a person. She  collected figurines. She  was learning to use CAD software. This was a person. He  was kind of an awesome lover. This was a person. He sang. He always had gum. This was a person. She couldn't grow a mustache. This was a person. He taught guitar. He was thrifty. This was a person. She was a wedding photographer. This was a person. He was rebuilding an engine. This was a person. He  always bought flowers for  his  desk. He just had  his car stereo repaired. This was a person. He was an awful driver. This was a person. He was a crossword whiz. He played piano. This was a person. He couldn't grow a mustache. This was a person. She picked up litter.  This was a person. He  was a plumber. This was a person. He  finished reading all of the works of Homer. This was a person. He  collected figurines. This was a person. He grew up on a farm.  This was a person. He always brought lunch. He threw a lot of parties. This was a person. She always brought reusable bags into the store. This was a person. He  scalped tickets This was a person. He  was a DJ. He wore a lot of jewelry. This was a person. He wanted to learn magic. This was a person. He loved cigarettes. This was a person. He was polite to salesmen. This was a person. She  got a terrible haircut a few days ago and shaved  her  head to escape from it. This was a person. He has two living parents. He  was a virgin. This was a person. She  was a mason. She couldn't grow a mustache. This was a person. She could play banjo. This was a person. He  was a mason. This was a person. He  was learning to speak French. This was a person. She was a good dancer. This was a person. He just had  his car stereo repaired. This was a person. She  was a translator. This was a person. She loved cigarettes. This was a person. He plays fantasy football. This was a person. She had an unfortunate nickname. This was a person. He never carried cash. This was a person. She wrote for the newspaper. This was a person. He always had gum. This was a person. He  was a plumber. He never carried cash. This was a person. She has two living parents. This was a person. He  was a historian. This was a person. He picked up litter.  This was a person. She was polite to telemarketers. This was a person. He never carried cash. This was a person. He  was training to run a marathon. He  was a teacher. This was a person. He was good to people. This was a person. She was divorced. This was a person. He  only ever had sex with one person. This was a person. He had extensions. He had a green thumb. This was a person. He ate a lot of fiber. He never finished the book club book. This was a person. She chewed gum constantly. She loved wine. This was a person. He helped strangers. He didn't give a damn about food. This was a person. He talked during movies. This was a person. She  had a personal injury lawsuit working its way through the courts. This was a person. She always brought reusable bags into the store. She was cockeyed. This was a person. He was good at job interviews. This was a person. She loved to fish. This was a person. She loved wine. She had extensions. This was a person. She snored. This was a person. She took a lot of photos. This was a person. He loved James Bond movies. He was the richest of  his friends. This was a person. She was divorced. She could play harmonica. This was a person. He just had the bandages removed from  plastic surgery. This was a person. He ate a lot of hot dogs. This was a person. He helped people. He wrote for the newspaper. This was a person. He sang. This was a person. She lived on breakfast bars. She loved nachos. This was a person. She could play trumpet. This was a person. She was good at job interviews. She loved wine. This was a person. He excelled at woodworking. This was a person. She had a lot of Beatles records. This was a person. She  was awaiting judgement for a DUI last month. This was a person. She played a lot of social card games.  This was a person. She always had gum. She knew how to get free satelittle television. This was a person. He  was afraid of flying. He  was a tailor. This was a person. He was working  his  way through all of the shows on Netflix. This was a person. She watched a lot of sports on TV, but never played them  herself. This was a person. He  was a mason. He was always in a hurry. This was a person. He had a baby boy. This was a person. He grew up on a farm.  This was a person. She  was learning to use CAD software. This was a person. She once robbed a bank. This was a person. She  was learning to use CAD software. This was a person. She ate a lot of fiber. This was a person. She loved cigarettes. She was sporty. This was a person. He had a lot of Beatles records. He was divorced. This was a person. He grew up on a farm.  This was a person. She had a twin. This was a person. He had bonsai trees. This was a person. She  collected figurines. This was a person. He led the choir. This was a person. He had braces on  his  teeth. This was a person. He loved pot. This was a person. She played a lot of social card games.  She spends a lot of time watching tennis. This was a person. She had a podcast. This was a person. She  called in sick to work 9 times last month and was written up at work. This was a person. He went to the horseraces. This was a person. She was a crossword whiz. This was a person. She wore a lot of hats.  She picked up litter.  This was a person. He was a wedding photographer. This was a person. He loved wine. This was a person. She sang. This was a person. He  was kind of an awesome lover. He was always in a hurry. This was a person. She was polite to telemarketers. This was a person. She  was afraid of flying. This was a person. She loved to fish. This was a person. She was gluten intolerant. This was a person. She abused cars. She was diabetic. This was a person. He  did open mike.

View a different tragedy with the Disaster Visualization Tool

Jonestown | The Titanic | Kent State Shootings | My Lai | Lockerbie bombing | Kent State Shootings | Tiananmen Square Massacre | The Banana massacre | The Boyd Massacre | Mountain Meadows massacre | Kfar Etzion Massacre | Sharpeville Massacre | The Miami Showband Massacre | The Novocherkassk massacre | Tokyo Subway Sarin attack | Sinking of the Titanic | The Happy Land Fire | Brooklyn Bridge stampede | 1990 Pilgrim Stampede | Luxor hot air balloon crash |

Mouse-over body descriptions are randomly generated, intended to inject humanity into the raw number of dead. It cannot accurately represent the actual people who died in the tragedy.

  The Oatmeal Markup | Antiques Roadshow - The Ultimate "Neat Stuff" Show | Iphone vs. Kia | Let us Dilute that For You | Razor and Blades Business Model | Short-Circuiting the Facebook Tease Video Link | Other Websites Besides Healthcare.org which are Broken | Visualizing the Price of a Television | Personal account of working for commision at Banker's Life Insurance | The Three Problems with Child Car Seats | How Much Time is Really Left in the Basketball Game? | Who Uses Their Turn Signal? | Other Web Problems not related to Healthcare.org | The Cross-Section of a Couch | Comparing the Price of Used Car to the Price of a New Car | Rental Car Keys are Horrible | The Actual Amount of Time it Takes | Incorrect Shelf Prices at Walmart | Two Prices for Auto Body Repair | Roadside Sobriety Test | Cash in your Pennies | Get it Together Walmart | Price Increases at Fast Food Restaurants | Yard Sale is Shoe Store Scam | Disaster Casualties Visualization Tool | Walmart vs Target: 2013 | The 146 Drugs in Walmart's $4 Prescription Drug Plan | Email Concealer Codes | accumulating credit card debt | Selling a Structured Settlement | The Torn-up Credit Card Application ! Kirby Vacuum Cleaners
  • Photographic Height/Weight Chart
  • The Weight of Clothing

  • Cockeyed home page | Contact | Terms and Conditions | Updated February 27, 2013   Copyright 2013 Cockeyed.com