10Be able totransform the datausing the variousmethods toproduce a model.1Create afrequencytableBe able to usetransformedequations topredict values21193Be able to findthe lower andupper fencesto determine ifoutliers existBe able to testthe assumptionthat the data islinear using aresidual plot.Be able toname theexplanatoryand responsevariables178Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able todescribe a scatterplot in terms ofstrength, directionand form.4Find theleastsquaresregressionline.Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)7616Be able toroundnumbersappropriately112523Be able tofindpercentages1215Interpret they-intercept ofa regressionline.18145Plot the leastsquaresregressionline on ascatter plot.Interpret thecoefficient ofdetermination.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.2013Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.24Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotInterpret theslope of aregressionline.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able to find Zscores andknow when Z-Scores areappropriate touse.Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing22Be able tocompare box-plots in terms oftheir shape,centre andspread.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation29Know what astructuralchange is andwhat effect ithas on datamodelling10Be able totransform the datausing the variousmethods toproduce a model.1Create afrequencytableBe able to usetransformedequations topredict values21193Be able to findthe lower andupper fencesto determine ifoutliers existBe able to testthe assumptionthat the data islinear using aresidual plot.Be able toname theexplanatoryand responsevariables178Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able todescribe a scatterplot in terms ofstrength, directionand form.4Find theleastsquaresregressionline.Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)7616Be able toroundnumbersappropriately112523Be able tofindpercentages1215Interpret they-intercept ofa regressionline.18145Plot the leastsquaresregressionline on ascatter plot.Interpret thecoefficient ofdetermination.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.2013Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.24Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotInterpret theslope of aregressionline.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able to find Zscores andknow when Z-Scores areappropriate touse.Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing22Be able tocompare box-plots in terms oftheir shape,centre andspread.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation29Know what astructuralchange is andwhat effect ithas on datamodelling

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. 10
  2. Be able to transform the data using the various methods to produce a model.
  3. 1
  4. Create a frequency table
  5. Be able to use transformed equations to predict values
  6. 21
  7. 19
  8. 3
  9. Be able to find the lower and upper fences to determine if outliers exist
  10. Be able to test the assumption that the data is linear using a residual plot.
  11. Be able to name the explanatory and response variables
  12. 17
  13. 8
  14. Difference between Numerical continuous, Numerical discrete, Categorical ordinal and Categorial nominal
  15. Be able to describe a scatter plot in terms of strength, direction and form.
  16. 4
  17. Find the least squares regression line.
  18. Know to set the axes scales so that the data is effectively displayed (uses most of the available space)
  19. 7
  20. 6
  21. 16
  22. Be able to round numbers appropriately
  23. 11
  24. 25
  25. 23
  26. Be able to find percentages
  27. 12
  28. 15
  29. Interpret the y-intercept of a regression line.
  30. 18
  31. 14
  32. 5
  33. Plot the least squares regression line on a scatter plot.
  34. Interpret the coefficient of determination.
  35. Be able to correctly identify suitable transformations in an attempt to linearise the data.
  36. 20
  37. 13
  38. Be able to describe a box-plot in terms of it’s shape, centre and spread. Know not to use the range.
  39. 24
  40. Know when to use the different data displays Bar Chart, Segmented Bar Chart, Histogram, Box-Plot, Stem & leaf, scatter plot
  41. Interpret the slope of a regression line.
  42. Be able to create a Bar Chart, Segmented Bar Chart, Histogram, Box-Plot or a Stem & leaf, scatter plot
  43. Be able to find Z scores and know when Z-Scores are appropriate to use.
  44. Be able to find if there is an association using a two-way table by first converting to percentages then comparing
  45. 22
  46. Be able to compare box-plots in terms of their shape, centre and spread.
  47. Be able to discuss the validity of predictions in regards to interpolation and extrapolation
  48. 2
  49. 9
  50. Know what a structural change is and what effect it has on data modelling