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

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