FliesdronesStarwarsfanHas aGitHubknows 3TaylorSwiftsongsHas workedin a cleanlab (on landor on a ship)DogpersonDoeslakesciencePrefersto codein RHas useda weatherballoonDrove acar >1hour toget hereDid fieldwork inthe lastyearWorkswithlidarWorkswithcitizenscientistsHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingIshungryright nowLives >2hoursdrive tothe oceanHas used asun-photometerWorkswithradarKnows moreaboutpolarimetrythan owningthe sunglassesWriteswikipediaarticlesHasa catFilters alot ofseawaterDoesNOT liketo teachbut has toHas beento thePacificOceanFlewhere ona planeHasa dogHas beenat sea for>1 weekClimberHas beenat sea for>1 weekDoes adistancesportKnowswhat asundog isScubadivesHasinteractedwith a CTD-RosetteSpeaks>2languagesHas beento theAtlanticOceanMovedhousewithin thelast yearDoes alot ofoutreachCan tell afield workdisasterstoryHas beento theSouthernOceanHas doneairbornescienceHas beento aconcert inlast monthHasconsideredbecomingan astronautPrefersto codein pythonLovesaerosolsKnowswhat asundog isKnows amagictrickPrefers tocode inMATLABPlays amusicalinstrumentIs anatmosphericscientistHas beento theArcticOceanDoesnot likepizzaModels(data orfashion)Plays amusicalinstrumentFliesdronesStarwarsfanHas aGitHubknows 3TaylorSwiftsongsHas workedin a cleanlab (on landor on a ship)DogpersonDoeslakesciencePrefersto codein RHas useda weatherballoonDrove acar >1hour toget hereDid fieldwork inthe lastyearWorkswithlidarWorkswithcitizenscientistsHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingIshungryright nowLives >2hoursdrive tothe oceanHas used asun-photometerWorkswithradarKnows moreaboutpolarimetrythan owningthe sunglassesWriteswikipediaarticlesHasa catFilters alot ofseawaterDoesNOT liketo teachbut has toHas beento thePacificOceanFlewhere ona planeHasa dogHas beenat sea for>1 weekClimberHas beenat sea for>1 weekDoes adistancesportKnowswhat asundog isScubadivesHasinteractedwith a CTD-RosetteSpeaks>2languagesHas beento theAtlanticOceanMovedhousewithin thelast yearDoes alot ofoutreachCan tell afield workdisasterstoryHas beento theSouthernOceanHas doneairbornescienceHas beento aconcert inlast monthHasconsideredbecomingan astronautPrefersto codein pythonLovesaerosolsKnowswhat asundog isKnows amagictrickPrefers tocode inMATLABPlays amusicalinstrumentIs anatmosphericscientistHas beento theArcticOceanDoesnot likepizzaModels(data orfashion)Plays amusicalinstrument

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