Achievement objective S6-1

Indicators

• Uses the statistical enquiry cycle to conduct investigations:
  • Poses investigative questions.
  • Selects, uses and justifies variables and their measures to use in order to solve a problem. For example, if investigating how to improve the school canteen, students need to decide what ‘improve’ means and select data measures to capture improvement.
  • Selects and uses appropriate sampling methods, for example, systematic and simple random techniques (names drawn from a hat, dice, or random number generators).
  • Uses a variety of data collection methods, such as web survey, face-to-face questionnaire, and automated computer logs.
  • Collects and manages data.
  • Uses appropriate statistical graphs and tables to explore the data and communicates relevant detail and overall distributions.
• Explores summary, comparative, bivariate, and time series data:
  • Links multiple representations and sees the connections between them.
  • Writes and presents a concise and informative report that includes communicating features in context; relevant summary statistics, graphs and tables to support the findings of the investigation; quantitative and qualitative statements; informal inferences about a population from a sample; justified conclusions.

What is new/changed?

• Justifying variables and measures used.
• Looking at the different sources of variation, for example, measurement variation.
• Random sampling.
• Sampling variation.
• Informal inferences using informal decision criteria as evidence for making a claim which is based on an understanding of sampling variation.
• Alternative explanations for observed patterns in the data.
• Contextual knowledge plays an important role in the entire statistical enquiry cycle.

Possible context elaborations

• CensusAtSchool – data collected by students, about students, for students – investigating comparative and bivariate situations using the CensusAtSchool database. For example, Do the bag weights of year 11 girls tend to be heavier than the bag weights of year 11 boys in the 2009 CensusAtSchool survey? Is there a relationship between heights of students and their neck circumference?
• Investigate the relationship between memory recall before learning memory recall skills and memory recall after learning memory skills.
• Growing scatterplots – uses CensusAtSchool data and looks at relationships between neck and wrist circumferences:
  • Teaching notes

  • Growing scatterplots (Word, 318 KB)

  • Data cards (PDF, 14 KB)

  • Scatter plot grid (Word, 259 KB)

• Sleeping sheep – collecting reaction times, using a web-based application, for comparison:
  • Teaching notes

  • Sleeping sheep or are you a turbo-charged cheetah? (Word, 839 KB)

  • Instruction sheet for sheep reaction times (Word, 1 MB)

  • Sleeping sheep

• You can’t fool me by giving me a cheap cola. Explores experiments and comparisons:
  • Example of student performance

  • You can’t fool me by giving me a cheap cola! (Word, 121 KB)

• Do boy babies tend to be heavier at birth than girl babies? Comparisons using dot plots and box plots:
  • Example of student performance

  • Baby weights (Word, 124 KB)

  • Baby weights fathom file (Unknown Binary File, 13 KB)

  • Baby weights spreadsheet (Excel, 36 KB)

• Does practice make perfect? Relationships and comparisons using box plots and scatter plots:
  • Example of student performance

  • Does practice make perfect? (Word, 172 KB)

• Activity: 100m sprint times
• Activity: Water woes
• Activity: Culturally locating our students in the class

• Appropriate graphing: Using appropriate statistical displays (starter activity).
• Arms and feet: Bivariate investigation using inside arm length and foot length.
• Big foot stands tall: Bivariate investigation about height and foot length.
• Bivariate investigations
• Comparing writing speeds: Comparison and bivariate investigations around writing speeds with dominant and non-dominant hand and writing backwards.
• Power jump: Bivariate investigation around power jumps.

Assessment for qualifications

NCEA achievement standards at level 1 and 2 have been aligned to the New Zealand Curriculum. Please ensure that you are using the correct version of the standards by going to the NZQA website.

Aligned level 3 achievement standards will be registered by NZQA for use in 2013.

Full information on the level 3 draft standards and the alignment process can be found on NCEA on TKI.

The following achievement standard(s) could assess learning outcomes from this AO.

• AS91035 Mathematics and statistics 1.10 Investigate a given multivariate data set using the statistical enquiry cycle
• AS91036 Mathematics and statistics 1.11 Investigate bivariate numerical data using the statistical enquiry cycle

Refer to the draft standards matrix.

Last updated September 25, 2012

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