We made it. We have read ACARA’s entire idiotic mathematics curriculum, and we’ve completed the Complete Awfullest Works. Meaning, soon, we’ll be on to Stage Two. But first, following on from Number and Algebra and Measurement and Space and Statistics, we have the post for the awfullest Probability lines.
The Probability stream is, of course, awful, but the awfulness is notably different in character from that of the Statistics. Whereas the statistics is a homogeneous gruel of “data”, with the only mathematical substance being the tiny, tasteless raisins of “median” and its kin, the probability stream has just enough substance to be consistently, solidly stupid.
Note that the Probability stream only begins in Year 3 since, unlike Algebra, the kids need to know a little before considering such concepts.
identify practical activities and everyday events involving chance; describe possible outcomes and events as ‘likely’ or ‘unlikely’ and identify some events as ‘certain’ or ‘impossible’ explaining reasoning (AC9M3P01)
classifying a list of everyday events or sorting a set of event cards according to how likely they are to happen, using the language of chance and giving reasons for classifications; discussing how impossible outcomes cannot ever happen, uncertain outcomes are affected by chance as they may or may not happen whereas certain events must always happen, so they are not affected by chance (AC9M3P01)
conduct repeated chance experiments to observe relationships between outcomes; identify and describe the variation in results (AC9M4P02)
playing games such as Noughts and Crosses or First to 20 and deciding if it makes a difference who goes first and whether you can use a particular strategy to increase your chances of winning (AC9M4P02)
list the possible outcomes of chance experiments involving equally likely outcomes and compare to those which are not equally likely (AC9M5P01)
experimenting with and comparing the outcomes of spinners with equal-coloured regions compared to unequal regions; responding to questions such as “How does this spinner differ to one where each of the colours has an equal chance of occurring?”, giving reasons (AC9M5P02)
listing the different possible outcomes for rolling a dice and using a scale to locate the relative probability by considering the chance of more or less than for each possible event ; for example, the probability of getting a number greater than 4 (AC9M6P01)
conduct repeated chance experiments and run simulations with an increasing number of trials using digital tools; compare observations with expected results and discuss the effect on variation of increasing the number of trials (AC9M6P02)
identify the sample space for single-stage events; assign probabilities to the outcomes of these events and predict relative frequencies for related events (AC9M7P01)
exploring and observing First Nations Australian children’s instructive games; for example, Koara from the Jawi and Bardi Peoples of Sunday Island in Western Australia, to investigate probability, predicting outcomes for an event and comparing with increasingly larger numbers of trials, and between observed and expected results (AC9M7P02)
recognise that complementary events have a combined probability of one; use this relationship to calculate probabilities in applied contexts (AC9M8P01)
describing events using language of “at least”, exclusive “or” (A or B but not both), inclusive “or” (A or B or both) and “and” (AC9M8P02)
list all outcomes for compound events both with and without replacement, using lists, tree diagrams, tables or arrays; assign probabilities to outcomes (AC9M9P01)
discussing two-step chance experiments, such as the game of Heads and tails, describing the different outcomes and their related probabilities (AC9M9P01)
design and conduct repeated chance experiments and simulations using digital tools to model conditional probability and interpret results (AC9M10P02)
recognising that an event can be dependent on another event and that this will affect the way its probability is calculated (AC9M10P02)
YEAR 10 OPTIONAL
counting principles, and factorial notation as a representation that provides efficient counting in multiplicative contexts, including calculations of probabilities
performing calculations on numbers expressed in factorial form, such as to evaluate the number of possible arrangements of n objects in a row, r of which are identical, for example 5 objects, 3 of which are identical, can be arranged in a row in different ways