Find theleastsquaresregressionline.Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able todescribe a scatterplot in terms ofstrength, directionand form.Be able to usetransformedequations topredict valuesBe able toname theexplanatoryand responsevariablesBe able tofindpercentagesInterpret theslope of aregressionline.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able totransform the datausing the variousmethods toproduce a model.Be able to find Zscores andknow when Z-Scores areappropriate touse.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotInterpret they-intercept ofa regressionline.Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able tocompare box-plots in terms oftheir shape,centre andspread.Know what astructuralchange is andwhat effect ithas on datamodellingBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able toroundnumbersappropriatelyPlot the leastsquaresregressionline on ascatter plot.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationCreate afrequencytableBe able to findthe lower andupper fencesto determine ifoutliers existInterpret thecoefficient ofdetermination.Know the differencebetween Numericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe able to testthe assumptionthat the data islinear using aresidual plot.Find theleastsquaresregressionline.Know to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able todescribe a scatterplot in terms ofstrength, directionand form.Be able to usetransformedequations topredict valuesBe able toname theexplanatoryand responsevariablesBe able tofindpercentagesInterpret theslope of aregressionline.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able totransform the datausing the variousmethods toproduce a model.Be able to find Zscores andknow when Z-Scores areappropriate touse.Know when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotInterpret they-intercept ofa regressionline.Be able to describea box-plot in termsof it’s shape, centreand spread. Knownot to use therange.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotBe able tocompare box-plots in terms oftheir shape,centre andspread.Know what astructuralchange is andwhat effect ithas on datamodellingBe able to find ifthere is anassociation using atwo-way table byfirst converting topercentages thencomparingBe able toroundnumbersappropriatelyPlot the leastsquaresregressionline on ascatter plot.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationCreate afrequencytableBe able to findthe lower andupper fencesto determine ifoutliers existInterpret thecoefficient ofdetermination.Know the differencebetween Numericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalBe 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. Find the least squares regression line.
  2. Know to set the axes scales so that the data is effectively displayed (uses most of the available space)
  3. Be able to describe a scatter plot in terms of strength, direction and form.
  4. Be able to use transformed equations to predict values
  5. Be able to name the explanatory and response variables
  6. Be able to find percentages
  7. Interpret the slope of a regression line.
  8. Be able to correctly identify suitable transformations in an attempt to linearise the data.
  9. Be able to transform the data using the various methods to produce a model.
  10. Be able to find Z scores and know when Z-Scores are appropriate to use.
  11. Know when to use the different data displays Bar Chart, Segmented Bar Chart, Histogram, Box-Plot, Stem & leaf, scatter plot
  12. Interpret the y-intercept of a regression line.
  13. Be able to describe a box-plot in terms of it’s shape, centre and spread. Know not to use the range.
  14. Be able to create a Bar Chart, Segmented Bar Chart, Histogram, Box-Plot or a Stem & leaf, scatter plot
  15. Be able to compare box-plots in terms of their shape, centre and spread.
  16. Know what a structural change is and what effect it has on data modelling
  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 round numbers appropriately
  19. Plot the least squares regression line on a scatter plot.
  20. Be able to discuss the validity of predictions in regards to interpolation and extrapolation
  21. Create a frequency table
  22. Be able to find the lower and upper fences to determine if outliers exist
  23. Interpret the coefficient of determination.
  24. Know the difference between Numerical continuous, Numerical discrete, Categorical ordinal and Categorial nominal
  25. Be able to test the assumption that the data is linear using a residual plot.