Knows howto calculatea percentagechangeKnowswhat abox plotrepresents Cancalculate asimplecorrelationcoefficientHasconductedbasic datacleaningtasksHasattended adata sciencebootcampHasexperiencewith cloudcomputingplatformsKnowswhat ahistogramis used forHasdeployedmachinelearningmodelsHascoded inPythonHas donedatavisualisationPursuing adegree indata scienceor analyticsCan identifytrends in atime seriesdatasetHascodedin RKnows howto create apie chart inExcelKnows howto importdata into aspreadsheetor databaseHasattended adata sciencemeetup orconferenceHas built adashboardusingTableau orPower BIHasexperiencewithclusteringalgorithmsHas used pivottables for datasummarizationHas usedExcel fordataanalysisUnderstandsthe conceptof data typesHasexperiencewithpredictivemodelingCaninterpretA/B testresultsCandescribe theprocess ofhypothesistestingKnowswhat adict is inPythonKnows howto create abar chart inExcelHas donedataanalysisCan explainthe conceptof datanormalizationCan explainmachinelearningconceptsCan explainthe conceptof overfittingin machinelearningCan interpreta basicregressionanalysisHascontributed toopen-sourcedata scienceprojectsFreeCan explainthe differencebetweenmean andmedianCanidentifyoutliers ina datasetHascreated abasic lineplotKnows howto calculatea percentagechangeKnowswhat abox plotrepresents Cancalculate asimplecorrelationcoefficientHasconductedbasic datacleaningtasksHasattended adata sciencebootcampHasexperiencewith cloudcomputingplatformsKnowswhat ahistogramis used forHasdeployedmachinelearningmodelsHascoded inPythonHas donedatavisualisationPursuing adegree indata scienceor analyticsCan identifytrends in atime seriesdatasetHascodedin RKnows howto create apie chart inExcelKnows howto importdata into aspreadsheetor databaseHasattended adata sciencemeetup orconferenceHas built adashboardusingTableau orPower BIHasexperiencewithclusteringalgorithmsHas used pivottables for datasummarizationHas usedExcel fordataanalysisUnderstandsthe conceptof data typesHasexperiencewithpredictivemodelingCaninterpretA/B testresultsCandescribe theprocess ofhypothesistestingKnowswhat adict is inPythonKnows howto create abar chart inExcelHas donedataanalysisCan explainthe conceptof datanormalizationCan explainmachinelearningconceptsCan explainthe conceptof overfittingin machinelearningCan interpreta basicregressionanalysisHascontributed toopen-sourcedata scienceprojectsFreeCan explainthe differencebetweenmean andmedianCanidentifyoutliers ina datasetHascreated abasic lineplot

Data Analytics Bingo - 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. Knows how to calculate a percentage change
  2. Knows what a box plot represents
  3. Can calculate a simple correlation coefficient
  4. Has conducted basic data cleaning tasks
  5. Has attended a data science bootcamp
  6. Has experience with cloud computing platforms
  7. Knows what a histogram is used for
  8. Has deployed machine learning models
  9. Has coded in Python
  10. Has done data visualisation
  11. Pursuing a degree in data science or analytics
  12. Can identify trends in a time series dataset
  13. Has coded in R
  14. Knows how to create a pie chart in Excel
  15. Knows how to import data into a spreadsheet or database
  16. Has attended a data science meetup or conference
  17. Has built a dashboard using Tableau or Power BI
  18. Has experience with clustering algorithms
  19. Has used pivot tables for data summarization
  20. Has used Excel for data analysis
  21. Understands the concept of data types
  22. Has experience with predictive modeling
  23. Can interpret A/B test results
  24. Can describe the process of hypothesis testing
  25. Knows what a dict is in Python
  26. Knows how to create a bar chart in Excel
  27. Has done data analysis
  28. Can explain the concept of data normalization
  29. Can explain machine learning concepts
  30. Can explain the concept of overfitting in machine learning
  31. Can interpret a basic regression analysis
  32. Has contributed to open-source data science projects
  33. Free
  34. Can explain the difference between mean and median
  35. Can identify outliers in a dataset
  36. Has created a basic line plot