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

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