Ishungryright nowPlays amusicalinstrumentHasa catCan tell afield workdisasterstoryHas beento theSouthernOceanHas beenat sea for>1 weekClimberFilters alot ofseawaterDoes adistancesportModels(data orfashion)Hasconsideredbecomingan astronautHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingKnows moreaboutpolarimetrythan owningthe sunglassesPrefers tocode inMATLABHas used asun-photometerHas beenat sea for>1 weekHas beento thePacificOceanDogpersonIs anatmosphericscientistHasinteractedwith a CTD-RosetteHas workedin a cleanlab (on landor on a ship)Prefersto codein pythonHas beento aconcert inlast monthFilters alot ofseawaterWorkswithradarHasa dogKnowswhat asundog isHas aGitHubHas useda weatherballoonFlewhere ona planeDid fieldwork inthe lastyearknows 3TaylorSwiftsongsDoesNOT liketo teachbut has toWorkswithcitizenscientistsWorkswithlidarKnows amagictrickHas beento theArcticOceanDoeslakescienceHas beento theAtlanticOceanHas doneairbornescienceFliesdronesMovedhousewithin thelast yearPlays amusicalinstrumentWriteswikipediaarticlesPrefersto codein RStarwarsfanDoesnot likepizzaDoes alot ofoutreachLives >2hoursdrive tothe oceanSpeaks>2languagesLovesaerosolsScubadivesDrove acar >1hour toget hereIshungryright nowPlays amusicalinstrumentHasa catCan tell afield workdisasterstoryHas beento theSouthernOceanHas beenat sea for>1 weekClimberFilters alot ofseawaterDoes adistancesportModels(data orfashion)Hasconsideredbecomingan astronautHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingKnows moreaboutpolarimetrythan owningthe sunglassesPrefers tocode inMATLABHas used asun-photometerHas beenat sea for>1 weekHas beento thePacificOceanDogpersonIs anatmosphericscientistHasinteractedwith a CTD-RosetteHas workedin a cleanlab (on landor on a ship)Prefersto codein pythonHas beento aconcert inlast monthFilters alot ofseawaterWorkswithradarHasa dogKnowswhat asundog isHas aGitHubHas useda weatherballoonFlewhere ona planeDid fieldwork inthe lastyearknows 3TaylorSwiftsongsDoesNOT liketo teachbut has toWorkswithcitizenscientistsWorkswithlidarKnows amagictrickHas beento theArcticOceanDoeslakescienceHas beento theAtlanticOceanHas doneairbornescienceFliesdronesMovedhousewithin thelast yearPlays amusicalinstrumentWriteswikipediaarticlesPrefersto codein RStarwarsfanDoesnot likepizzaDoes alot ofoutreachLives >2hoursdrive tothe oceanSpeaks>2languagesLovesaerosolsScubadivesDrove acar >1hour toget here

Human Bingo: Find someone who... - Call List

(Print) Use this randomly generated list as your call list when playing the game. There is no need to say the BINGO column name. Place some kind of mark (like an X, a checkmark, a dot, tally mark, etc) on each cell as you announce it, to keep track. You can also cut out each item, place them in a bag and pull words from the bag.


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  1. Is hungry right now
  2. Plays a musical instrument
  3. Has a cat
  4. Can tell a field work disaster story
  5. Has been to the Southern Ocean
  6. Has been at sea for >1 week
  7. Climber
  8. Filters a lot of seawater
  9. Does a distance sport
  10. Models (data or fashion)
  11. Has considered becoming an astronaut
  12. Has called into a PACE Science & Applications Team (SAT) Meeting
  13. Knows more about polarimetry than owning the sunglasses
  14. Prefers to code in MATLAB
  15. Has used a sun-photometer
  16. Has been at sea for >1 week
  17. Has been to the Pacific Ocean
  18. Dog person
  19. Is an atmospheric scientist
  20. Has interacted with a CTD-Rosette
  21. Has worked in a clean lab (on land or on a ship)
  22. Prefers to code in python
  23. Has been to a concert in last month
  24. Filters a lot of seawater
  25. Works with radar
  26. Has a dog
  27. Knows what a sundog is
  28. Has a GitHub
  29. Has used a weather balloon
  30. Flew here on a plane
  31. Did field work in the last year
  32. knows 3 Taylor Swift songs
  33. Does NOT like to teach but has to
  34. Works with citizen scientists
  35. Works with lidar
  36. Knows a magic trick
  37. Has been to the Arctic Ocean
  38. Does lake science
  39. Has been to the Atlantic Ocean
  40. Has done airborne science
  41. Flies drones
  42. Moved house within the last year
  43. Plays a musical instrument
  44. Writes wikipedia articles
  45. Prefers to code in R
  46. Star wars fan
  47. Does not like pizza
  48. Does a lot of outreach
  49. Lives >2 hours drive to the ocean
  50. Speaks >2 languages
  51. Loves aerosols
  52. Scuba dives
  53. Drove a car >1 hour to get here