Be able to usetransformedequations topredict values21249Interpret they-intercept ofa regressionline.Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able todescribe a scatterplot in terms ofstrength, directionand form.Interpret theslope of aregressionline.7Be able to findthe lower andupper fencesto determine ifoutliers exist1015Be able totransform the datausing the variousmethods toproduce a model.17Create afrequencytableBe able toroundnumbersappropriatelyKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)4Be able to testthe assumptionthat the data islinear using aresidual plot.22Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal26Be able toname theexplanatoryand responsevariablesFind theleastsquaresregressionline.Know what astructuralchange is andwhat effect ithas on datamodellingBe able tocompare box-plots in terms oftheir shape,centre andspread.58116Plot 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 Zscores andknow when Z-Scores areappropriate touse.1332318Be able tofindpercentages20Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing11Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation12Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plot2519Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.14Interpret thecoefficient ofdetermination.Be able to usetransformedequations topredict values21249Interpret they-intercept ofa regressionline.Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able todescribe a scatterplot in terms ofstrength, directionand form.Interpret theslope of aregressionline.7Be able to findthe lower andupper fencesto determine ifoutliers exist1015Be able totransform the datausing the variousmethods toproduce a model.17Create afrequencytableBe able toroundnumbersappropriatelyKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)4Be able to testthe assumptionthat the data islinear using aresidual plot.22Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal26Be able toname theexplanatoryand responsevariablesFind theleastsquaresregressionline.Know what astructuralchange is andwhat effect ithas on datamodellingBe able tocompare box-plots in terms oftheir shape,centre andspread.58116Plot 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 Zscores andknow when Z-Scores areappropriate touse.1332318Be able tofindpercentages20Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing11Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation12Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plot2519Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.14Interpret thecoefficient ofdetermination.

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