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

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