Mountain Meadows massacre Tragedy Casualties Visualization Tool - Cockeyed.com

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. She called in sick to work 9 times last month and was written up at work.

This was a person. She had a personal injury lawsuit working its way through the courts.

This was a person. She had tropical fish.

This was a person. He was afraid of the water. He knew a lot of cops.

This was a person. She was a virgin.

This was a person. He slept around.

This was a person. She was a Mac evangelist.

This was a person. He was a cat person.

This was a person. He just had his car stereo repaired.

This was a person. She was a hoarder.

This was a person. He had a bunch of tattoos.

This was a person. She has four overdue books.

This was a person. She survived cancer.

This was a person. He was lactose intolerant.

This was a person. He never carried cash.

This was a person. He had VD. He was rebuilding an engine.

This was a person. He plays fantasy football. He was a loner.

This was a person. He was a teacher.

This was a person. He made scrapbooks.

This was a person. He was a teacher.

This was a person. She helped strangers. She was really good at geography.

This was a person. She was a skilled woodcarver.

This was a person. She was always in a hurry.

This was a person. He made pie.

This was a person. He was a secret Buddahist. He always brought lunch.

This was a person. She was a hoarder.

This was a person. He had an awesome home theatre.

This was a person. She never ate breakfast.

This was a person. He was an awful driver.

This was a person. He was a wedding photographer.

This was a person. He was divorced. He wanted to learn magic.

This was a person. He was lactose intolerant.

This was a person. He was a scout leader.

This was a person. She had an unfortunate nickname.

This was a person. He never carried cash.

This was a person. He helped strangers.

This was a person. He wore bow ties. He had lice.

This was a person. She was a teacher. She was a drunk.

This was a person. He wore a lot of jewelry.

This was a person. He volunteered at a middle school, because he had a crush on one of the other tutors.

This was a person. She had a baby boy.

This was a person. She could juggle. She survived cancer.

This was a person. She had tropical fish. She could play banjo.

This was a person. She had just paid a crapload of money to get teeth fixed.

This was a person. She went to church.

This was a person. She made pie.

This was a person. She played chess.

This was a person. She just had the bandages removed from plastic surgery.

This was a person. He was working his way through all of the shows on Netflix.

This was a person. She just had the bandages removed from plastic surgery.

This was a person. She overtipped.

This was a person. He can't watch the end of T2 without crying

This was a person. He didn't have a family. He had VD.

This was a person. He took careful notes after every meal. He was a secret Buddahist.

This was a person. He was very good at cleaning.

This was a person. She was polite to telemarketers.

This was a person. He had VD.

This was a person. He was a Mac evangelist.

This was a person. She was a cheapskate.

This was a person. He made his own beer and was kind of stingy with it.

This was a person. He loved cigarettes.

This was a person. He was a translator. He was afraid of the water.

This was a person. He was very careful about conserving gasoline.

This was a person. She never drank coffee.

This was a person. He was a poet.

This was a person. He was working his way through all of the shows on Netflix.

This was a person. She smoked pot at music festivals.

This was a person. She was thrifty. She could play harmonica.

This was a person. She was rough and tumble.

This was a person. She could play trumpet.

This was a person. He was good to people.

This was a person. She had a hangover yesterday.

This was a person. He was a skilled woodcarver. He wanted to learn magic.

This was a person. She could play banjo.

This was a person. She was a dog person. She wanted to learn magic.

This was a person. He wore Spandex.

This was a person. She loved chocolate. She was a good dancer.

This was a person. She loved Elvis.

This was a person. She played World of Warcraft

This was a person. She wore a lot of jewelry.

This was a person. He was polite to telemarketers.

This was a person. He was very careful about conserving gasoline.

This was a person. He always brought lunch.

This was a person. He spends a lot of time watching tennis.

This was a person. He had a bunch of cameras.

This was a person. She snored.

This was a person. He had an unfortunate nickname. He chewed nicotine gum.

This was a person. He was a hoarder. He wore a lot of hats.

This was a person. He was a virgin.

This was a person. He snored.

This was a person. She always had gum.

This was a person. She played a lot of social card games. She had a green thumb.

This was a person. She was a Mac evangelist.

This was a person. He did open mike.

This was a person. She knew how to get free satelittle television.

This was a person. She could play trumpet. She ate a lot of chinese food.

This was a person. She kept buying vegetables, even though they always just went bad in her fridge. She was working her way through all of the shows on Netflix.

This was a person. He made scrapbooks.

This was a person. He was allergic to peanuts. He always had a clean car.

This was a person. He was gluten intolerant.

This was a person. She played piano.

This was a person. She was a drunk.

This was a person. She never carried cash.

This was a person. He was learning to use CAD software. He loved James Bond movies.

This was a person. He ate a lot of kale.

This was a person. He was a wedding photographer. He loved pot.

This was a person. She could play harmonica. She ate a lot of chinese food.

This was a person. She was a good dancer.

This was a person. She was a mason.

This was a person. She was a trivia master.

This was a person. She has four overdue books.

This was a person. He ate a lot of hot dogs. He always had a clean car.

This was a person. He finished reading all of the works of Homer.

This was a person. She just had her car stereo repaired. She never raised hervoice.

This was a person. She plays fantasy football.

This was a person. She got thrown off of a golf course. She excelled at woodworking.

This was a person. She had a podcast.

This was a person. He took a lot of photos.

This was a person. He never ate breakfast. He could play cricket.

This was a person. She was sleeping with her ex.

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