Hasinteractedwith a CTD-RosettePrefersto codein RHas beento thePacificOceanKnows moreaboutpolarimetrythan owningthe sunglassesDrove acar >1hour toget hereIs anatmosphericscientistHas beento theSouthernOceanWorkswithlidarScubadivesHas used asun-photometerFilters alot ofseawaterHasconsideredbecomingan astronautSpeaks>2languagesDoesNOT liketo teachbut has toHasa dogknows 3TaylorSwiftsongsMovedhousewithin thelast yearClimberDid fieldwork inthe lastyearDogpersonHas beenat sea for>1 weekDoes alot ofoutreachDoesnot likepizzaFliesdronesHas aGitHubWorkswithradarHas beento theAtlanticOceanStarwarsfanHas doneairbornescienceHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingHas useda weatherballoonHas beenat sea for>1 weekWorkswithcitizenscientistsKnows amagictrickIshungryright nowDoeslakescienceHas beento theArcticOceanFlewhere ona planeModels(data orfashion)Filters alot ofseawaterLives >2hoursdrive tothe oceanHas workedin a cleanlab (on landor on a ship)Plays amusicalinstrumentPrefers tocode inMATLABKnowswhat asundog isPlays amusicalinstrumentDoes adistancesportHas beento aconcert inlast monthLovesaerosolsHasa catWriteswikipediaarticlesPrefersto codein pythonCan tell afield workdisasterstoryHasinteractedwith a CTD-RosettePrefersto codein RHas beento thePacificOceanKnows moreaboutpolarimetrythan owningthe sunglassesDrove acar >1hour toget hereIs anatmosphericscientistHas beento theSouthernOceanWorkswithlidarScubadivesHas used asun-photometerFilters alot ofseawaterHasconsideredbecomingan astronautSpeaks>2languagesDoesNOT liketo teachbut has toHasa dogknows 3TaylorSwiftsongsMovedhousewithin thelast yearClimberDid fieldwork inthe lastyearDogpersonHas beenat sea for>1 weekDoes alot ofoutreachDoesnot likepizzaFliesdronesHas aGitHubWorkswithradarHas beento theAtlanticOceanStarwarsfanHas doneairbornescienceHas called intoa PACEScience &ApplicationsTeam (SAT)MeetingHas useda weatherballoonHas beenat sea for>1 weekWorkswithcitizenscientistsKnows amagictrickIshungryright nowDoeslakescienceHas beento theArcticOceanFlewhere ona planeModels(data orfashion)Filters alot ofseawaterLives >2hoursdrive tothe oceanHas workedin a cleanlab (on landor on a ship)Plays amusicalinstrumentPrefers tocode inMATLABKnowswhat asundog isPlays amusicalinstrumentDoes adistancesportHas beento aconcert inlast monthLovesaerosolsHasa catWriteswikipediaarticlesPrefersto codein pythonCan tell afield workdisasterstory

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