Be able tocompare box-plots in terms oftheir shape,centre andspread.212Be able todescribe a scatterplot in terms ofstrength, directionand form.6Be able toroundnumbersappropriatelyDifference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal242018Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)14Be able to usetransformedequations topredict valuesBe able totransform the datausing the variousmethods toproduce a model.Be able to findthe lower andupper fencesto determine ifoutliers exist22Be able tofindpercentages4191Plot the leastsquaresregressionline on ascatter plot.Be able toname theexplanatoryand responsevariables16Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationKnow when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotFind theleastsquaresregressionline.Interpret they-intercept ofa regressionline.Know what astructuralchange is andwhat effect ithas on datamodellingBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing13Be able to testthe assumptionthat the data islinear using aresidual plot.Create afrequencytable11217Interpret thecoefficient ofdetermination.Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.175152593Interpret theslope of aregressionline.10Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plot823Be able tocompare box-plots in terms oftheir shape,centre andspread.212Be able todescribe a scatterplot in terms ofstrength, directionand form.6Be able toroundnumbersappropriatelyDifference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal242018Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)14Be able to usetransformedequations topredict valuesBe able totransform the datausing the variousmethods toproduce a model.Be able to findthe lower andupper fencesto determine ifoutliers exist22Be able tofindpercentages4191Plot the leastsquaresregressionline on ascatter plot.Be able toname theexplanatoryand responsevariables16Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationKnow when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotFind theleastsquaresregressionline.Interpret they-intercept ofa regressionline.Know what astructuralchange is andwhat effect ithas on datamodellingBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing13Be able to testthe assumptionthat the data islinear using aresidual plot.Create afrequencytable11217Interpret thecoefficient ofdetermination.Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.175152593Interpret theslope of aregressionline.10Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plot823

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