24Interpret they-intercept ofa regressionline.Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal14217Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.413255Be able toname theexplanatoryand responsevariables11837Create afrequencytableInterpret theslope of aregressionline.Be able tofindpercentagesBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.8Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationBe able totransform the datausing the variousmethods toproduce a model.Be able to usetransformedequations topredict values16Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)2120Plot the leastsquaresregressionline on ascatter plot.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able tocompare box-plots in terms oftheir shape,centre andspread.10196Be able toroundnumbersappropriately22Interpret thecoefficient ofdetermination.Be able todescribe a scatterplot in terms ofstrength, directionand form.912Be able to testthe assumptionthat the data islinear using aresidual plot.15Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to findthe lower andupper fencesto determine ifoutliers existKnow what astructuralchange is andwhat effect ithas on datamodellingFind theleastsquaresregressionline.112324Interpret they-intercept ofa regressionline.Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal14217Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.413255Be able toname theexplanatoryand responsevariables11837Create afrequencytableInterpret theslope of aregressionline.Be able tofindpercentagesBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.8Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationBe able totransform the datausing the variousmethods toproduce a model.Be able to usetransformedequations topredict values16Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)2120Plot the leastsquaresregressionline on ascatter plot.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able tocompare box-plots in terms oftheir shape,centre andspread.10196Be able toroundnumbersappropriately22Interpret thecoefficient ofdetermination.Be able todescribe a scatterplot in terms ofstrength, directionand form.912Be able to testthe assumptionthat the data islinear using aresidual plot.15Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to findthe lower andupper fencesto determine ifoutliers existKnow what astructuralchange is andwhat effect ithas on datamodellingFind theleastsquaresregressionline.1123

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