Know what astructuralchange is andwhat effect ithas on datamodelling6Create afrequencytableBe able toname theexplanatoryand responsevariables25Be able totransform the datausing the variousmethods toproduce a model.9Interpret they-intercept ofa regressionline.17Be able to usetransformedequations topredict values1Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing224Interpret theslope of aregressionline.15Be able toroundnumbersappropriatelyBe able to testthe assumptionthat the data islinear using aresidual plot.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotPlot the leastsquaresregressionline on ascatter plot.12Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able todescribe a scatterplot in terms ofstrength, directionand form.19Be able tofindpercentages3Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Find theleastsquaresregressionline.2311Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation13Interpret thecoefficient ofdetermination.14Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal1082124162052187Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able tocompare box-plots in terms oftheir shape,centre andspread.Be able to findthe lower andupper fencesto determine ifoutliers existKnow what astructuralchange is andwhat effect ithas on datamodelling6Create afrequencytableBe able toname theexplanatoryand responsevariables25Be able totransform the datausing the variousmethods toproduce a model.9Interpret they-intercept ofa regressionline.17Be able to usetransformedequations topredict values1Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing224Interpret theslope of aregressionline.15Be able toroundnumbersappropriatelyBe able to testthe assumptionthat the data islinear using aresidual plot.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotPlot the leastsquaresregressionline on ascatter plot.12Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able todescribe a scatterplot in terms ofstrength, directionand form.19Be able tofindpercentages3Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Find theleastsquaresregressionline.2311Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation13Interpret thecoefficient ofdetermination.14Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal1082124162052187Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able tocompare box-plots in terms oftheir shape,centre andspread.Be able to findthe lower andupper fencesto determine ifoutliers exist

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