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

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