2Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal16Be able todescribe a scatterplot in terms ofstrength, directionand form.191711Interpret theslope of aregressionline.14Create afrequencytable126Interpret thecoefficient ofdetermination.52110Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able toname theexplanatoryand responsevariables2518Know what astructuralchange is andwhat effect ithas on datamodellingInterpret they-intercept ofa regressionline.24Be able totransform the datausing the variousmethods toproduce a model.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able toroundnumbersappropriately2315131Be able to findthe lower andupper fencesto determine ifoutliers exist822Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able tofindpercentagesBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.720Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationFind theleastsquaresregressionline.Plot the leastsquaresregressionline on ascatter plot.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plot9Be able to usetransformedequations topredict valuesBe able to testthe assumptionthat the data islinear using aresidual plot.3Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plot4Be able tocompare box-plots in terms oftheir shape,centre andspread.2Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal16Be able todescribe a scatterplot in terms ofstrength, directionand form.191711Interpret theslope of aregressionline.14Create afrequencytable126Interpret thecoefficient ofdetermination.52110Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able toname theexplanatoryand responsevariables2518Know what astructuralchange is andwhat effect ithas on datamodellingInterpret they-intercept ofa regressionline.24Be able totransform the datausing the variousmethods toproduce a model.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able toroundnumbersappropriately2315131Be able to findthe lower andupper fencesto determine ifoutliers exist822Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able tofindpercentagesBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.720Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationFind theleastsquaresregressionline.Plot the leastsquaresregressionline on ascatter plot.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plot9Be able to usetransformedequations topredict valuesBe able to testthe assumptionthat the data islinear using aresidual plot.3Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plot4Be 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. 2
  2. Difference between Numerical continuous, Numerical discrete, Categorical ordinal and Categorial nominal
  3. 16
  4. Be able to describe a scatter plot in terms of strength, direction and form.
  5. 19
  6. 17
  7. 11
  8. Interpret the slope of a regression line.
  9. 14
  10. Create a frequency table
  11. 12
  12. 6
  13. Interpret the coefficient of determination.
  14. 5
  15. 21
  16. 10
  17. Be able to find Z scores and know when Z-Scores are appropriate to use.
  18. Be able to name the explanatory and response variables
  19. 25
  20. 18
  21. Know what a structural change is and what effect it has on data modelling
  22. Interpret the y-intercept of a regression line.
  23. 24
  24. Be able to transform the data using the various methods to produce a model.
  25. Be able to correctly identify suitable transformations in an attempt to linearise the data.
  26. Be able to round numbers appropriately
  27. 23
  28. 15
  29. 13
  30. 1
  31. Be able to find the lower and upper fences to determine if outliers exist
  32. 8
  33. 22
  34. Know to set the axes scales so that the data is effectively displayed (uses most of the available space)
  35. Be able to find if there is an association using a two-way table by first converting to percentages then comparing
  36. Be able to find percentages
  37. Be able to describe a box-plot in terms of it’s shape, centre and spread. Know not to use the range.
  38. 7
  39. 20
  40. Be able to discuss the validity of predictions in regards to interpolation and extrapolation
  41. Find the least squares regression line.
  42. Plot the least squares regression line on a scatter plot.
  43. Be able to create a Bar Chart, Segmented Bar Chart, Histogram, Box-Plot or a Stem & leaf, scatter plot
  44. 9
  45. Be able to use transformed equations to predict values
  46. Be able to test the assumption that the data is linear using a residual plot.
  47. 3
  48. Know when to use the different data displays Bar Chart, Segmented Bar Chart, Histogram, Box-Plot, Stem & leaf, scatter plot
  49. 4
  50. Be able to compare box-plots in terms of their shape, centre and spread.