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

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 name the explanatory and response variables
  2. Find the least squares regression line.
  3. Interpret the slope of a regression line.
  4. Plot the least squares regression line on a scatter plot.
  5. Create a frequency table
  6. Be able to create a Bar Chart, Segmented Bar Chart, Histogram, Box-Plot or a Stem & leaf, scatter plot
  7. Be able to find the lower and upper fences to determine if outliers exist
  8. Interpret the y-intercept of a regression line.
  9. Be able to find Z scores and know when Z-Scores are appropriate to use.
  10. Interpret the coefficient of determination.
  11. Be able to use transformed equations to predict values
  12. Be able to test the assumption that the data is linear using a residual plot.
  13. Know what a structural change is and what effect it has on data modelling
  14. Know the difference between Numerical continuous, Numerical discrete, Categorical ordinal and Categorial nominal
  15. Be able to correctly identify suitable transformations in an attempt to linearise the data.
  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 compare box-plots in terms of their shape, centre and spread.
  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 round numbers appropriately
  21. Be able to transform the data using the various methods to produce a model.
  22. Know to set the axes scales so that the data is effectively displayed (uses most of the available space)
  23. Know when to use the different data displays Bar Chart, Segmented Bar Chart, Histogram, Box-Plot, Stem & leaf, scatter plot
  24. Be able to discuss the validity of predictions in regards to interpolation and extrapolation
  25. Be able to describe a scatter plot in terms of strength, direction and form.