Be able to find Zscores andknow when Z-Scores areappropriate touse.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able tocompare box-plots in terms oftheir shape,centre andspread.Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able to discussthe validity ofpredictions inregards tointerpolation andextrapolationBe able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able to findthe lower andupper fencesto determine ifoutliers existBe able toname theexplanatoryand responsevariablesInterpret they-intercept ofa regressionline.Create afrequencytableBe able to usetransformedequations topredict valuesInterpret thecoefficient ofdetermination.Be able totransform the datausing the variousmethods toproduce a model.Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able todescribe a scatterplot in terms ofstrength, directionand form.Interpret theslope of aregressionline.Know the differencebetween Numericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Plot the leastsquaresregressionline on ascatter plot.Be able to testthe assumptionthat the data islinear using aresidual plot.Know what astructuralchange is andwhat effect ithas on datamodellingBe able tofindpercentagesBe able toroundnumbersappropriatelyFind theleastsquaresregressionline.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotBe able to find Zscores andknow when Z-Scores areappropriate touse.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able tocompare box-plots in terms oftheir shape,centre andspread.Be able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able to discussthe validity ofpredictions inregards tointerpolation andextrapolationBe able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able to findthe lower andupper fencesto determine ifoutliers existBe able toname theexplanatoryand responsevariablesInterpret they-intercept ofa regressionline.Create afrequencytableBe able to usetransformedequations topredict valuesInterpret thecoefficient ofdetermination.Be able totransform the datausing the variousmethods toproduce a model.Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able todescribe a scatterplot in terms ofstrength, directionand form.Interpret theslope of aregressionline.Know the differencebetween Numericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Plot the leastsquaresregressionline on ascatter plot.Be able to testthe assumptionthat the data islinear using aresidual plot.Know what astructuralchange is andwhat effect ithas on datamodellingBe able tofindpercentagesBe able toroundnumbersappropriatelyFind theleastsquaresregressionline.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter 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 Z scores and know when Z-Scores are appropriate to use.
  2. Be able to correctly identify suitable transformations in an attempt to linearise the data.
  3. Be able to compare box-plots in terms of their shape, centre and spread.
  4. Be able to find if there is an association using a two-way table by first converting to percentages then comparing
  5. Be able to discuss the validity of predictions in regards to interpolation and extrapolation
  6. Be able to create a Bar Chart, Segmented Bar Chart, Histogram, Box-Plot or a Stem & leaf, scatter plot
  7. Be able to find the lower and upper fences to determine if outliers exist
  8. Be able to name the explanatory and response variables
  9. Interpret the y-intercept of a regression line.
  10. Create a frequency table
  11. Be able to use transformed equations to predict values
  12. Interpret the coefficient of determination.
  13. Be able to transform the data using the various methods to produce a model.
  14. Know to set the axes scales so that the data is effectively displayed (uses most of the available space)
  15. Be able to describe a scatter plot in terms of strength, direction and form.
  16. Interpret the slope of a regression line.
  17. Know the difference between Numerical continuous, Numerical discrete, Categorical ordinal and Categorial nominal
  18. Be able to describe a box-plot in terms of it’s shape, centre and spread. Know not to use the range.
  19. Plot the least squares regression line on a scatter plot.
  20. Be able to test the assumption that the data is linear using a residual plot.
  21. Know what a structural change is and what effect it has on data modelling
  22. Be able to find percentages
  23. Be able to round numbers appropriately
  24. Find the least squares regression line.
  25. Know when to use the different data displays Bar Chart, Segmented Bar Chart, Histogram, Box-Plot, Stem & leaf, scatter plot