16Be able to find Zscores andknow when Z-Scores areappropriate touse.Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal314Be able to testthe assumptionthat the data islinear using aresidual plot.Be able to usetransformedequations topredict valuesBe able to discussthe validity ofpredictions inregards tointerpolation andextrapolation5Interpret they-intercept ofa regressionline.Be able tofindpercentages210Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plot781317121Be able toname theexplanatoryand responsevariablesKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Know what astructuralchange is andwhat effect ithas on datamodelling92524Interpret thecoefficient ofdetermination.Interpret theslope of aregressionline.15421Be able tocompare box-plots in terms oftheir shape,centre andspread.Plot the leastsquaresregressionline on ascatter plot.Create afrequencytable20Be able to findthe lower andupper fencesto determine ifoutliers existBe able totransform the datausing the variousmethods toproduce a model.196Find theleastsquaresregressionline.Be able todescribe a scatterplot in terms ofstrength, directionand form.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plot18Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.2211Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing23Be able toroundnumbersappropriately16Be able to find Zscores andknow when Z-Scores areappropriate touse.Difference betweenNumericalcontinuous,Numerical discrete,Categorical ordinaland Categorialnominal314Be able to testthe assumptionthat the data islinear using aresidual plot.Be able to usetransformedequations topredict valuesBe able to discussthe validity ofpredictions inregards tointerpolation andextrapolation5Interpret they-intercept ofa regressionline.Be able tofindpercentages210Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plot781317121Be able toname theexplanatoryand responsevariablesKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Know what astructuralchange is andwhat effect ithas on datamodelling92524Interpret thecoefficient ofdetermination.Interpret theslope of aregressionline.15421Be able tocompare box-plots in terms oftheir shape,centre andspread.Plot the leastsquaresregressionline on ascatter plot.Create afrequencytable20Be able to findthe lower andupper fencesto determine ifoutliers existBe able totransform the datausing the variousmethods toproduce a model.196Find theleastsquaresregressionline.Be able todescribe a scatterplot in terms ofstrength, directionand form.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plot18Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.2211Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparing23Be able toroundnumbersappropriately

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.


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