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

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