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

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