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

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