Be able todescribe a scatterplot in terms ofstrength, directionand form.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationBe able toroundnumbersappropriatelyBe 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.Know what astructuralchange is andwhat effect ithas on datamodellingKnow when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotInterpret they-intercept ofa regressionline.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 thencomparingCreate afrequencytableBe able to findthe lower andupper fencesto determine ifoutliers existBe able to testthe assumptionthat the data islinear using aresidual plot.Interpret thecoefficient ofdetermination.Be able to find Zscores andknow when Z-Scores areappropriate touse.Interpret theslope of aregressionline.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotFind theleastsquaresregressionline.Be able to usetransformedequations topredict valuesKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able toname theexplanatoryand responsevariablesBe able tofindpercentagesKnow the differencebetween Numericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalPlot the leastsquaresregressionline on ascatter plot.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.Be able todescribe a scatterplot in terms ofstrength, directionand form.Be able to discussthe validity ofpredictions inregards tointerpolation andextrapolationBe able toroundnumbersappropriatelyBe 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.Know what astructuralchange is andwhat effect ithas on datamodellingKnow when to usethe different datadisplays Bar Chart,Segmented BarChart, Histogram,Box-Plot, Stem &leaf, scatter plotInterpret they-intercept ofa regressionline.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 thencomparingCreate afrequencytableBe able to findthe lower andupper fencesto determine ifoutliers existBe able to testthe assumptionthat the data islinear using aresidual plot.Interpret thecoefficient ofdetermination.Be able to find Zscores andknow when Z-Scores areappropriate touse.Interpret theslope of aregressionline.Be able to create aBar Chart,Segmented BarChart, Histogram,Box-Plot or a Stem& leaf, scatter plotFind theleastsquaresregressionline.Be able to usetransformedequations topredict valuesKnow to set theaxes scales sothat the data iseffectivelydisplayed (usesmost of theavailable space)Be able toname theexplanatoryand responsevariablesBe able tofindpercentagesKnow the differencebetween Numericalcontinuous,Numerical discrete,Categorical ordinaland CategorialnominalPlot the leastsquaresregressionline on ascatter plot.Be able tocorrectly identifysuitabletransformations inan attempt tolinearise the data.

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.


1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
  1. Be able to describe a scatter plot in terms of strength, direction and form.
  2. Be able to discuss the validity of predictions in regards to interpolation and extrapolation
  3. Be able to round numbers appropriately
  4. Be able to describe a box-plot in terms of it’s shape, centre and spread. Know not to use the range.
  5. Be able to transform the data using the various methods to produce a model.
  6. Know what a structural change is and what effect it has on data modelling
  7. Know when to use the different data displays Bar Chart, Segmented Bar Chart, Histogram, Box-Plot, Stem & leaf, scatter plot
  8. Interpret the y-intercept of a regression line.
  9. Be able to compare box-plots in terms of their shape, centre and spread.
  10. Be able to find if there is an association using a two-way table by first converting to percentages then comparing
  11. Create a frequency table
  12. Be able to find the lower and upper fences to determine if outliers exist
  13. Be able to test the assumption that the data is linear using a residual plot.
  14. Interpret the coefficient of determination.
  15. Be able to find Z scores and know when Z-Scores are appropriate to use.
  16. Interpret the slope of a regression line.
  17. Be able to create a Bar Chart, Segmented Bar Chart, Histogram, Box-Plot or a Stem & leaf, scatter plot
  18. Find the least squares regression line.
  19. Be able to use transformed equations to predict values
  20. Know to set the axes scales so that the data is effectively displayed (uses most of the available space)
  21. Be able to name the explanatory and response variables
  22. Be able to find percentages
  23. Know the difference between Numerical continuous, Numerical discrete, Categorical ordinal and Categorial nominal
  24. Plot the least squares regression line on a scatter plot.
  25. Be able to correctly identify suitable transformations in an attempt to linearise the data.