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

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