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

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