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

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