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

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