The Awfullest Australian Curriculum Statistics Lines

This one is different. It is ostensibly a year-by-year selection of the worst statistics lines chosen from the Complete Awfullest Works. Unlike for Number and Algebra and Measurement and Space, however, this is effectively impossible. Nothing similar, or anything, properly works for Statistics. Even the lines chosen for the Complete Awfullest Works were chosen largely at random.

The Statistics stream is so bad, so vague and thin and aimless and repetitive, the only proper way to appreciate the badness is to read the entire thing. There is likely just one person in Australia stubborn enough to do that: Merchant-Ivory has its Joe Queenan, and ACARA has its Marty. You’re welcome.

We shall write soon about the Statistics stream, and about other absurd specifics of the Curriculum. But for now, for what it’s worth, here is our nominal selection of the awfullest Statistics lines.


collect, sort and compare data represented by objects and images in response to given investigative questions that relate to familiar situations (AC9MFST01)

exploring what and how information from the environment is collected and used by First Nations Australians to predict weather events (AC9MFST01)


discussing methods of collecting data to answer a question, such as “What types of rubbish are found in the playground?”, sharing ideas and trying out some of the suggested methods; reviewing the data collected and explaining how they might change the way they collect data next time (AC9M1ST01)

represent collected data for a categorical variable using one-to-one displays and digital tools where appropriate; compare the data using frequencies and discuss the findings (AC9M1ST02)


acquire data for categorical variables through surveys, observation, experiment and using digital tools; sort data into relevant categories and display data using lists and tables (AC9M2ST01)

using digital tools to create picture graphs to represent data using one-to-one correspondence, deciding on an appropriate title for the graph and considering whether the categories of data are appropriate for the context (AC9M2ST02)


acquire data for categorical and discrete numerical variables to address a question of interest or purpose by observing, collecting and accessing data sets; record the data using appropriate methods including frequency tables and spreadsheets (AC9M3ST01)

using efficient ways to collect and record data; for example, written surveys, online surveys, polling the class using interactive digital mediums, and representing and reporting the results of investigations (AC9M3ST01)


acquiring samples of data using practical activities, observations or repeated chance experiments, recording data using tally charts, digital tables or spread sheets, graphing, discussing and comparing the results using a column graph (AC9M4ST01)

conduct statistical investigations, collecting data through survey responses and other methods; record and display data using digital tools; interpret the data and communicate the results (AC9M4ST03)


using digital systems to validate data; for example, recognising the difference between numerical, text and date formats in spreadsheets; setting data types in a spreadsheet to make sure a date is input correctly (AC9M5ST01)

interpret line graphs representing change over time; discuss the relationships that are represented and conclusions that can be made (AC9M5ST02)


interpret and compare data sets for ordinal and nominal categorical, discrete and continuous numerical variables using comparative displays or visualisations and digital tools; compare distributions in terms of mode, range and shape (AC9M6ST01)

using technology to access data sets and graphing software to construct side-by-side column graphs or stacked line graphs; comparing data sets that are grouped by gender, year level, age group or other variables and discussing findings (AC9M6ST01)


create different types of numerical data displays including stem-and-leaf plots using software where appropriate; describe and compare the distribution of data, commenting on the shape, centre and spread including outliers and determining the range, median, mean and mode (AC9M7ST02)

connecting features of the data display; for example, highest frequency, clusters, gaps, symmetry or skewness, to the mode, range and median, and the question in context; describing the shape of distributions using terms such as “positive skew”, “negative skew”, “symmetric” and “bi-modal” and discussing the location of the median and mean on these distributions (AC9M7ST02)


using digital tools to simulate repeated sampling of the same population, such as heights or arm spans of students, recording and comparing means, median and range of data between samples (AC9M8ST03)

plan and conduct statistical investigations involving samples of a population; use ethical and fair methods to make inferences about the population and report findings, acknowledging uncertainty (AC9M8ST04)


exploring potential cultural bias relating to First Nations Australians by critically analysing sampling techniques in statistical reports (AC9M9ST02)

choose appropriate forms of display or visualisation for a given type of data; justify selections and interpret displays for a given context (AC9M9ST04)


using digital tools to compare boxplots and histograms as displays of the same data in the light of the statistical questions being addressed and the effectiveness of the display in helping to answer the question (AC9M10ST02)

construct scatterplots and comment on the association between the 2 numerical variables in terms of strength, direction and linearity (AC9M10ST03)


measures of spread, their interpretation and usefulness with respect to different data distributions

comparing measures of spread for different data distributions, such as mean or median absolute deviations with standard deviations, and exploring the effect of outliers

20 Replies to “The Awfullest Australian Curriculum Statistics Lines”

  1. I will admit only reading the 7 to 10 content but I do agree that it is quite a task to persevere with the read-through in the hope that some “aha!” moment may come.

    The “technology” and “digital tools” seem to be driving half the bus but there is a fair measure of “bias” of one form or another.

    I don’t want to start a debate with anyone about when it is and is not appropriate to discuss bias in statistics, but my opinion is simply: if the teacher does not understand it, do not expect the students to understand.

    In this case, ACARA is playing the role of the teacher.

  2. Thank you for your sacrifice!

    Do you think the statistics curriculum version 9 is even more repetitive than the current one? I’m new to this and find it kind of confusing – this year I taught a statistics topic to Year 10, then Year 9, then to Year 7. Various times the students had acted like something was totally new, and I taught it thinking it was new to them. But then I found out they were supposed to have already done it the year before, and the year before that, and – now reading the curriculum – possibly the year before the year before that as well.

    There doesn’t seem to be a very clear sense (to me) of progression in Version 9 either. Looking at the Year 6 and Year 7, there’s a progression from “run simulations with an increasing number of trials using digital tools” to “run simulations with a large number of trials using digital tools”. That’s just the same thing twice.

    The worst lines for Year 7 show such a broad range of things, it makes me wonder how we would be expected to do all that in a meaningful way. What would that look like? How much time would they expect us to spend on it?

    Also, it’s weird how they have a definition of stem-and-leaf plots that describes back-to-back stem-and-leaf plots.

      1. Oh, don’t worry, there is simulation in statistics as well…

        But your point is a valid one: if 80% (rough estimate) of the content that gets taught overlaps in Years 7 to 10 is the issue that the content descriptors are too hard to follow or that students need this repetition to actually understand statistics?

        Let me know if you work it out…

          1. Yes, that is a general ACARA perversion. But at least in the maths, there is at least a little maths to be repeated. In stats, it’s just averages and their kin time after time after brain-drilling time.

    1. Thanks, wst. There are many, many examples of “same thing twice”. There’s almost nothing else. As to whether v9 is worse than v8, that’s a good question. Probably, but v8 is terrible as well.

      As to how “to do all that in a meaningful way”, there are two points to be made:

      1) It’s all puff. Just like “modelling” and “investigating” and “analysing”. None of it genuinely points to anything of substance. Most teachers know this.

      2) The smart teachers know that in a given year the entire stats topic is pointless, and should be given only the lippiest of lip service.

      1. Point 2 is sad, because a lot of students are very enthusiastic to learn about statistics. Honestly, I was surprised. And I think there are opportunities to do some interesting things. A lot of the work as a teacher is finding interesting yet simple enough data to talk about. It didn’t feel much like teaching mathematics though. I felt like I was teaching “out of field”, but I do when I teach calculator-studies and financial maths as well. Maybe that’s normal for all teachers.

        I originally rambled a bit about Year 4 probability and statistics and how it seems kind of advanced to me for kids who are still learning to skip-count by fractions: dependent vs independent events, describing the shape of distributions, etc., but then deleted a lot of my comment. I think that is taught in Year 10, and it made me wonder what they’re talking about in Year 4. Do you think there is a risk of leading students to have misconceptions by teaching things in a puffy way?

    2. When teachers try to fit the curriculum into the lesson time that they have they will often run out of time. Schools vary in how much time they allocate to maths. Because of the high overlap between content for year levels, probability and statistics gets to be the optional ‘if we get time for it’ part of the curriculum. My current year 10 class told me that the last time they did probability was in year 6.

      1. Which is very not good, since probability is more easily mathematical, and reinforces other aspects of the curriculum. School statistics, at least in a maths class, is necessarily junk; probability is not.

  3. I would like to see statistics removed from the mathematics curriculum. Instead one could easily develop a 4 unit strand on statistics for Years 11 and 12 that would be interesting, coherent, useful, with some depth. This could replace Foundation Mathematics.

    1. I think that it’s best for statistics to be removed completely from the curriculum, because even if VCAA somehow makes a brilliant statistics course or strand, a large amount of high school math teachers are so clueless that they would do students harm even if the curriculum was decent.

      The best option is probably to make statistics a compulsory first year subject for some majors like psychology or whatever other majors use statistics a lot.

      1. I’d have the statistics subject at school taught by well qualified statistics teachers, not necessarily mathematics teachers.

        1. At Year 7-10 level, I wonder if statistics fits just as well into humanities as mathematics. Could humanities teachers teach it?

          1. No. They could not.

            But Mathematics teachers are expected to teach History and Geography (and probably civics) if you believe all the new points of emphasis.

        2. “Well qualified” is quite a relative term in modern education…

          We have had a debate on this blog some years ago about the meaning of “suitably qualified” when it comes to Mathematics teachers. Something tells me it would be even less straight-forward with “statistics teachers”.

        3. I really doubt that enough of those (as in well knowledgeable statistics teachers, not teachers willing to teach statistics, or even teachers “qualified” to teach statistics) exist throughout the state to make a statistics subject that a large amount of schools could offer.

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