Be able tofindpercentages19Create afrequencytable2095312Be able todescribe a scatterplot in terms ofstrength, directionand form.Be able to find Zscores andknow when Z-Scores areappropriate touse.118Be able to usetransformedequations topredict values1562Be able toname theexplanatoryand responsevariablesBe able totransform the datausing the variousmethods toproduce a model.131417Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation21Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotFind theleastsquaresregressionline.11Know what astructuralchange is andwhat effect ithas on datamodellingBe able to testthe assumptionthat the data islinear using aresidual plot.Be able to findthe lower andupper fencesto determine ifoutliers existInterpret theslope of aregressionline.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.74101622Interpret thecoefficient ofdetermination.258Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Plot the leastsquaresregressionline on ascatter plot.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able toroundnumbersappropriately24Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Interpret they-intercept ofa regressionline.23Be able tocompare box-plots in terms oftheir shape,centre andspread.Be able tofindpercentages19Create afrequencytable2095312Be able todescribe a scatterplot in terms ofstrength, directionand form.Be able to find Zscores andknow when Z-Scores areappropriate touse.118Be able to usetransformedequations topredict values1562Be able toname theexplanatoryand responsevariablesBe able totransform the datausing the variousmethods toproduce a model.131417Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation21Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotFind theleastsquaresregressionline.11Know what astructuralchange is andwhat effect ithas on datamodellingBe able to testthe assumptionthat the data islinear using aresidual plot.Be able to findthe lower andupper fencesto determine ifoutliers existInterpret theslope of aregressionline.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.74101622Interpret thecoefficient ofdetermination.258Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Plot the leastsquaresregressionline on ascatter plot.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able toroundnumbersappropriately24Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Interpret they-intercept ofa regressionline.23Be able tocompare box-plots in terms oftheir shape,centre andspread.

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