1Be able to findthe lower andupper fencesto determine ifoutliers existBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able to usetransformedequations topredict values3Interpret they-intercept ofa regressionline.42522Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation1612Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.23Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plot20Be able tocompare box-plots in terms oftheir shape,centre andspread.Interpret thecoefficient ofdetermination.Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able todescribe a scatterplot in terms ofstrength, directionand form.Find theleastsquaresregressionline.19Know what astructuralchange is andwhat effect ithas on datamodellingBe able to testthe assumptionthat the data islinear using aresidual plot.7Be able toname theexplanatoryand responsevariablesBe able tofindpercentages15Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotCreate afrequencytable92Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able totransform the datausing the variousmethods toproduce a model.1710115Be able toroundnumbersappropriately6Interpret theslope of aregressionline.8Plot the leastsquaresregressionline on ascatter plot.Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal14132118Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing241Be able to findthe lower andupper fencesto determine ifoutliers existBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able to usetransformedequations topredict values3Interpret they-intercept ofa regressionline.42522Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation1612Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.23Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plot20Be able tocompare box-plots in terms oftheir shape,centre andspread.Interpret thecoefficient ofdetermination.Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able todescribe a scatterplot in terms ofstrength, directionand form.Find theleastsquaresregressionline.19Know what astructuralchange is andwhat effect ithas on datamodellingBe able to testthe assumptionthat the data islinear using aresidual plot.7Be able toname theexplanatoryand responsevariablesBe able tofindpercentages15Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotCreate afrequencytable92Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able totransform the datausing the variousmethods toproduce a model.1710115Be able toroundnumbersappropriately6Interpret theslope of aregressionline.8Plot the leastsquaresregressionline on ascatter plot.Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal14132118Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing24

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