Interpret thecoefficient ofdetermination.Be able to findthe lower andupper fencesto determine ifoutliers existBe able to testthe assumptionthat the data islinear using aresidual plot.611023227Create afrequencytable113Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able to find Zscores andknow when Z-Scores areappropriate touse.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plot24Interpret theslope of aregressionline.17Plot the leastsquaresregressionline on ascatter plot.25Be able toname theexplanatoryand responsevariables9516Be able toroundnumbersappropriatelyBe able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Know what astructuralchange is andwhat effect ithas on datamodelling8Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal4141913Find theleastsquaresregressionline.Be able to usetransformedequations topredict valuesKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able tofindpercentagesBe able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotInterpret they-intercept ofa regressionline.2Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation121521Be able totransform the datausing the variousmethods toproduce a model.Be able todescribe a scatterplot in terms ofstrength, directionand form.Be able tocompare box-plots in terms oftheir shape,centre andspread.Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing2018Interpret thecoefficient ofdetermination.Be able to findthe lower andupper fencesto determine ifoutliers existBe able to testthe assumptionthat the data islinear using aresidual plot.611023227Create afrequencytable113Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able to find Zscores andknow when Z-Scores areappropriate touse.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plot24Interpret theslope of aregressionline.17Plot the leastsquaresregressionline on ascatter plot.25Be able toname theexplanatoryand responsevariables9516Be able toroundnumbersappropriatelyBe able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Know what astructuralchange is andwhat effect ithas on datamodelling8Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal4141913Find theleastsquaresregressionline.Be able to usetransformedequations topredict valuesKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able tofindpercentagesBe able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotInterpret they-intercept ofa regressionline.2Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation121521Be able totransform the datausing the variousmethods toproduce a model.Be able todescribe a scatterplot in terms ofstrength, directionand form.Be able tocompare box-plots in terms oftheir shape,centre andspread.Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing2018

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