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

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