2311161Plot the leastsquaresregressionline on ascatter plot.Be able tocompare box-plots in terms oftheir shape,centre andspread.7Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Find theleastsquaresregressionline.81924Be able totransform the datausing the variousmethods toproduce a model.Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal2Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotInterpret theslope of aregressionline.Be able tofindpercentages6Be able todescribe a scatterplot in terms ofstrength, directionand form.9Be able toroundnumbersappropriatelyBe able to usetransformedequations topredict valuesKnow what astructuralchange is andwhat effect ithas on datamodelling20Interpret thecoefficient ofdetermination.1422Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)412Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation25Interpret they-intercept ofa regressionline.1310Be able to findthe lower andupper fencesto determine ifoutliers existBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing35Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to testthe assumptionthat the data islinear using aresidual plot.1518Create afrequencytableBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.2117Be able toname theexplanatoryand responsevariables2311161Plot the leastsquaresregressionline on ascatter plot.Be able tocompare box-plots in terms oftheir shape,centre andspread.7Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Find theleastsquaresregressionline.81924Be able totransform the datausing the variousmethods toproduce a model.Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal2Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotInterpret theslope of aregressionline.Be able tofindpercentages6Be able todescribe a scatterplot in terms ofstrength, directionand form.9Be able toroundnumbersappropriatelyBe able to usetransformedequations topredict valuesKnow what astructuralchange is andwhat effect ithas on datamodelling20Interpret thecoefficient ofdetermination.1422Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)412Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolation25Interpret they-intercept ofa regressionline.1310Be able to findthe lower andupper fencesto determine ifoutliers existBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing35Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to testthe assumptionthat the data islinear using aresidual plot.1518Create afrequencytableBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.2117Be able toname theexplanatoryand responsevariables

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