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

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