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

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