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

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