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

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