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

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