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

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