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

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