Keep away from horses

Achievement objectives

S5-2: Evaluate statistical investigations or probability activities undertaken by others, including data collection methods, choice of measures, and validity of findings.

Required materials

See Materials that come with this resource to download:

• Keep away from horses activity (.pdf)

Activity

Task: This statistical report (included in a downloadable file) on injury rates in various sports was prepared by a group of students for a school newsletter.

Evaluate the validity of their conclusions.

The following prompts illustrate how this activity can be structured around aspects of statistical literacy.

Data source

The section is about the reliability of the data sources being used.

• Are the data provided relevant to the claim posed in the report? (The report provides data about ACC claims of teenagers who play different sports.)
• Are the data sources acknowledged, and are these sources reliable? (The sources are given and are reliable organisations.)

Evidence for the claim

The section is about the validity of the data and how it is used to support the claim.

• Does the evidence provided justify the claim? (The report uses percentages of players getting injured rather than frequencies. This is a fairer way to calculate the injury rate. However, the injury data and numbers of players are not from the same cohort 15- to 19-year-olds and secondary students playing sport.)
• Is there evidence missing that would further validate the claim?
• Are there weaknesses in the evidence presented that include other explanations for variations in the data?

Strength of the claim

The section is about the adequacy of the data and other factors that may have influenced the findings.

• Is the data adequate to support the conclusions? (This includes issues about the sampling, such as size and representativeness.)
• Are some factors ignored in the claim? (The work samples raise issues about the omission of other dangerous sports, players who play more than one sport, the severity of the injuries, etc.).
• What further investigation is needed to support the claim?

Plan

The planning section is about how students will gather the data.

• How will I go about answering this question?
• What will I need to know?
• How will I find the data that I need? Is the data already available somewhere, or will I need to collect it?
• Have I considered ethics so that people’s permission is given, their data is safeguarded, and my data gathering does no harm to them?
• If I need to collect data, how will I measure the characteristic?
• How will I make sure the measurement is as accurate as possible and ‘fairly’ measures the characteristic?
• If I need to construct a survey, have I checked that my questions are clear and not leading (unbiased)? Have I trialled my questions on a few people first?
• What type of sample will I use? Can I justify why I chose that type of sample?
• How large will my sample be? Will my sample size be large enough, or do I need to increase or reduce it?
• Can I predict possible answers to my question even before I look at the data?
• What might my answer look like?

Data

The data section is concerned with how the data is managed and organised.

• What format will I use to organise my data as I gather it or retrieve it?
• How much time will it take to gather or retrieve my data? Have I got time to do it? Have my subjects had time to give me their data?
• What digital or written tools will help me organise my data? (Consider software and pencil and paper methods.)
• How will I protect the data I gather or retrieve so it is safe?
• How will I protect the privacy of the subjects who are trusting me with their data?
• Is some data ‘dirty’ (untrustworthy)? How will I clean my data?

Analysis

The analysis section is about exploring the data and reasoning with it.

• Have I reflected back on my question so I am clear on what I am trying to find out?
• Do I get ideas about patterns, differences, relationships, and trends from just ‘eyeballing’ the table of data?
• Are my important variables categorical, discrete numeric, or continuous (measurements)?
• How can I display different sortings of my data to look for patterns, differences, relationships, and trends? 
• What tools will help me to display the data in different ways? What ways are appropriate to my data and help answer my question?
• How might I describe the distribution(s)? What language might I use to describe what I see? (Symmetric/Assymmetric (Skewed), spike, trough, etc.)
• Are there differences among distributions in terms of centre, shape, and spread? Which measures of those features should I use?
• What variation can I see in my data? What might be the causes of that variation?
• Can I make preliminary statements about my findings, starting with “I noticed that...”
• Am I developing ideas about what the answer to my question might be?

Conclusion

The conclusion section is about answering the question in the problem section and providing reasons based on their analysis.

• Have I answered my original question? If not, why not?
• How might I convince someone else that I have answered the question?
• What displays best show what I have found out?
• Is my summary of findings clearly written so others can understand it?
• Have I used displays and measures to support my ideas?
• Do I go back to the context to suggest why the patterns, differences, relationships, or trends occur?
• Do I say about the limitations of what I have found out? What can I say, and what can’t I say?
• What strategies and tools proved the most useful in my inquiry?
• What other things have I learned, and what further questions do I have?