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