Be able toroundnumbersappropriatelyKnow when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to find Zscores andknow when Z-Scores areappropriate touse.Be able to usetransformedequations topredict valuesBe able totransform the datausing the variousmethods toproduce a model.Interpret they-intercept ofa regressionline.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able todescribe a scatterplot in terms ofstrength, directionand form.Be able to findthe lower andupper fencesto determine ifoutliers existBe able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotKnow what astructuralchange is andwhat effect ithas on datamodellingKnow the differencebetween Numericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able toname theexplanatoryand responsevariablesBe able tofindpercentagesBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able tocompare box-plots in terms oftheir shape,centre andspread.Find theleastsquaresregressionline.Interpret thecoefficient ofdetermination.Be able to testthe assumptionthat the data islinear using aresidual plot.Plot the leastsquaresregressionline on ascatter plot.Interpret theslope of aregressionline.Create afrequencytableKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able toroundnumbersappropriatelyKnow when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to find Zscores andknow when Z-Scores areappropriate touse.Be able to usetransformedequations topredict valuesBe able totransform the datausing the variousmethods toproduce a model.Interpret they-intercept ofa regressionline.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able todescribe a scatterplot in terms ofstrength, directionand form.Be able to findthe lower andupper fencesto determine ifoutliers existBe able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotKnow what astructuralchange is andwhat effect ithas on datamodellingKnow the differencebetween Numericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able toname theexplanatoryand responsevariablesBe able tofindpercentagesBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able tocompare box-plots in terms oftheir shape,centre andspread.Find theleastsquaresregressionline.Interpret thecoefficient ofdetermination.Be able to testthe assumptionthat the data islinear using aresidual plot.Plot the leastsquaresregressionline on ascatter plot.Interpret theslope of aregressionline.Create afrequencytableKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)

Summary Card 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. Be able to round numbers appropriately
  2. Know when to use the different data displays Bar Chart, Segmented Bar Chart, Histogram, Box-Plot, Stem & leaf, scatter plot
  3. Be able to find Z scores and know when Z-Scores are appropriate to use.
  4. Be able to use transformed equations to predict values
  5. Be able to transform the data using the various methods to produce a model.
  6. Interpret the y-intercept of a regression line.
  7. Be able to discuss the validity of predictions in regards to interpolation and extrapolation
  8. Be able to find if there is an association using a two-way table by first converting to percentages then comparing
  9. Be able to describe a scatter plot in terms of strength, direction and form.
  10. Be able to find the lower and upper fences to determine if outliers exist
  11. Be able to create a Bar Chart, Segmented Bar Chart, Histogram, Box-Plot or a Stem & leaf, scatter plot
  12. Know what a structural change is and what effect it has on data modelling
  13. Know the difference between Numerical continuous, Numerical discrete, Categorical ordinal and Categorial nominal
  14. Be able to name the explanatory and response variables
  15. Be able to find percentages
  16. Be able to describe a box-plot in terms of it’s shape, centre and spread. Know not to use the range.
  17. Be able to correctly identify suitable transformations in an attempt to linearise the data.
  18. Be able to compare box-plots in terms of their shape, centre and spread.
  19. Find the least squares regression line.
  20. Interpret the coefficient of determination.
  21. Be able to test the assumption that the data is linear using a residual plot.
  22. Plot the least squares regression line on a scatter plot.
  23. Interpret the slope of a regression line.
  24. Create a frequency table
  25. Know to set the axes scales so that the data is effectively displayed (uses most of the available space)