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

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