Statistics: Time to play
View Sequence overviewWhen investigating what is “best”, we first need to define what best means. This informs the data that we need to collect.
Whole class
Time to Play PowerPoint
Each group
Access to computers
Task
Take the students for a walk or play outside as a way to prepare for a whole class discussion. Return to the classroom for the class discussion.
Discuss:
- Was it a good time of day to play outside just now? Why, or why not?
- Students should justify their answers as to why it was or was not a good time to play outside.
- What is the “best time” of the day to play outside?
- Discuss that “best time” means there are times that will be better than others to play outside. Allow students to share and discuss some of their initial thinking on the “best time”. It is likely that students will start to use different variables to justify their comments (e.g. temperature, time of day).
- When we are deciding the best time to play outside, what factors impact our decision?
- Some of these variables that impact the “best time” will be based on opinion, such as times when I can play with my friends, or times when it is raining because I love to play in the rain. Other variables will be based on factual information such as when the temperature is lower in the middle of summer. Make a list on the board of the different factors to be considered (variables) that students come up with. You might have students distinguish between those that are fact and those that are opinion.
Explain that the class will specifically collect factual data on weather factors to determine the best time to play outside during school hours. The weather elements that the class investigates will be dependent on your geographical location and context. For example, humidity will be a significant factor for some areas of Australia, while temperature may be more significant for other areas.
Brainstorm weather factors that might impact the best time to play outside. Some might include:
- Temperature
- Rainfall
- Humidity
- Wind speed
- UV Index
Discuss as a class the most relevant factors given your geographical location and context. Decide on two or three factors to investigate to determine the best time to play outside.
We use secondary data through this sequence. Some secondary data is more readily available that other data. You might limit what options students can investigate based on the ease of access to the required data.
We use historical data accessed from the Bureau of Meteorology website through this sequence. The Bureau of Meteorology has ready access to historical data on the following elements for all locations across Australia:
- Temperature
- half-hourly actual temperature and “feels like” temperature for the most recent 5 days.
- maximum and minimum daily temperatures and monthly average temperatures across the years.
- Rainfall
- half-hourly rainfall measurements for the most recent 5 days.
- average daily or monthly rainfall temperatures across the years.
- Humidity: half-hourly humidity measurements for the most recent 5 days.
- Wind speed and wind gusts: half-hourly wind speed and wind gusts measurements for the most recent 5 days.
- UV Index: average annual, monthly and seasonal values of the UV Index.
You can request access to further data from the Bureau of Meteorology website (fees and charges may apply).
Historical data on UV Index can be accessed for a limited number of major Australian cities from Australian Radiation Protection and Nuclear Safety Agency (ARPANSA)
When is the “best time”?
What is the best time to play outside? The answer to this question is—it depends! The “best time” is dependent on many different variables. In this sequence students specifically look at external variables associated with weather and air qualities. The “best time” is also dependent on personal factors, such as times when I can play with my friends, or times when it is raining because I love to play in the rain.
More often than not in statistics, there is not one right answer. The answer is dependent on many different factors. Yet the questions we ask in school statistics often suggest that there is just one answer. For example, we often investigate questions like our class’s favourite colour or chocolate bar. Or we might ask analysis questions such as what is the most or least popular activity. The reality is that the answers to these questions can change from day to day, across contexts, or given different variables.
It is important that students realise that there is not a clear answer to many statistical investigations. At the end of an investigation, students should be comfortable with concluding that the answer is—it depends! This investigation will help them start to identify factors and data behind decisions.
What is the best time to play outside? The answer to this question is—it depends! The “best time” is dependent on many different variables. In this sequence students specifically look at external variables associated with weather and air qualities. The “best time” is also dependent on personal factors, such as times when I can play with my friends, or times when it is raining because I love to play in the rain.
More often than not in statistics, there is not one right answer. The answer is dependent on many different factors. Yet the questions we ask in school statistics often suggest that there is just one answer. For example, we often investigate questions like our class’s favourite colour or chocolate bar. Or we might ask analysis questions such as what is the most or least popular activity. The reality is that the answers to these questions can change from day to day, across contexts, or given different variables.
It is important that students realise that there is not a clear answer to many statistical investigations. At the end of an investigation, students should be comfortable with concluding that the answer is—it depends! This investigation will help them start to identify factors and data behind decisions.
Ask: What might be the best time to play outside today while we are at school?
This is the investigation question for the following two lessons. The question asks for the "best time to play outside today...". As you progress through the investigation, keep referring back to the best time to play outside on the day that you complete this particular lesson (Lesson 1).
Explain to the students that they will investigate the nominated weather element for the time of the year in their location. Discuss the sort of data that needs to be collected and how it can be collected. While some data can be collected using measuring tools that are more readily available (e.g. a thermometer to measure temperature), other factors require tools that are less accessible (e.g. a UV meter to measure the UV index). Explain that data will be collected online, in other words, students will be using secondary data.
Discuss with the students how this data can be accessed easily on the internet from many different websites, however not all of these websites provide reliable data. Establish that we need to access our data from a reputable source, and identify the Bureau of Meteorology website.
Divide the students into groups of 3-4 students and explain that each group will investigate just one of the weather elements that the class has chosen to investigate. Allocate a factor to each group or allow students to choose which one they will investigate.
Show the students how to access weather data from the Bureau of Meteorology website for your school’s location.
The Bureau holds a vast archive of weather observations, analyses and statistics.
A section of the Bureau of Meteorology website is designed for teachers and students - https://reg.bom.gov.au/climate/data-services/education.shtml
On this page you will find a section called “Weather planning”. Under the sub-heading “Within 24”, select “Current conditions”. Here you can search for the closest weather station to your school and access nearly 20 years of climate data.
This takes you to a new page - https://reg.bom.gov.au/places/
From this page you can search for the weather data for your specific location.
Allow students time to explore the Bureau’s website and the information that is available.
After students have had time to explore the website, convene a class discussion. Remind students that they are investigating the question What might be the best time to play outside today during school hours?. Show students slide 5 of Time to play PowerPoint. Discuss the questions that are posed, come to consensus on a plan for data collection, and record the decisions made by the class onto the slide for later reference.
- What information do we need to collect to answer the question?
- The information that we need to collect is the data on the weather elements. Emphasise that this information is “data”; this may not be immediately obvious to students.
- To answer the question What might be the best time to play outside today while we are at school? students will need to collect data over the course of the school day.
- How will we collect our data?
- The data will be collected from the Bureau of Meteorology website.
- How will we record our data?
- We suggest using a spreadsheet program like Microsoft Excel. Microsoft Excel is a useful tool for recording data, and it is easy to change between data representations, which will be important when students come to represent their collected data.
- There are many online tutorials on how to use Microsoft Excel if you or the students are unfamiliar with how to use the program to represent data.
Using digital tools
Spreadsheet programs such as Microsoft Excel are useful tools that allow students to clearly organise and represent their data. We should be teaching students when it is appropriate to use these tools and how to use these tools well. Organising and representing data is a very appropriate use of digital tools.
The reality is, that beyond the classroom, data collected from statistical investigations is rarely recorded or represented using pen and paper only. Nearly everything is done with computers. Datasets can be enormous and very messy, and we need digital tools to help us sort, clean, manage, represent and analyse data. Digital tools also allow us to do things that are not possible manually and simplifies other process and tasks. For example, the use of a tool like Excel in this task allows students to change between different representations quickly and easily. This helps students decide which form/s of representation are more or most appropriate, and to see the different stories that the representations tell.
Spreadsheet programs such as Microsoft Excel are useful tools that allow students to clearly organise and represent their data. We should be teaching students when it is appropriate to use these tools and how to use these tools well. Organising and representing data is a very appropriate use of digital tools.
The reality is, that beyond the classroom, data collected from statistical investigations is rarely recorded or represented using pen and paper only. Nearly everything is done with computers. Datasets can be enormous and very messy, and we need digital tools to help us sort, clean, manage, represent and analyse data. Digital tools also allow us to do things that are not possible manually and simplifies other process and tasks. For example, the use of a tool like Excel in this task allows students to change between different representations quickly and easily. This helps students decide which form/s of representation are more or most appropriate, and to see the different stories that the representations tell.
Is this data reliable?
We live in a data-saturated world. The internet means that we have ready access to a plethora of secondary data. Not all of this data is reliable. It's not uncommon for data to be presented in a misleading manner to support a specific narrative that may not reflect the entire truth.
With so much data, we must ensure the data we choose to use is reliable. This idea is reflected in the Statistics content descriptors for Year 5 in the Australian Curriculum: Mathematics. Content descriptor AC9M5ST01 states that students need to “acquire, validate and represent data…”. Do you see it there? Students should not just acquire and represent data; they must also validate it.
How can you determine if secondary data is reliable and valid? The best approach is to use data from reputable sources. In this context, students are gathering climate data, and with various narratives emerging around climate issues, it’s essential to rely on information from trusted sources.
The Bureau of Meteorology records data from weather stations right across the country. The Bureau requires accurate data to make future predictions about the weather. We might joke that we cannot trust the Bureau because their weather predictions are not 100% accurate, but these inaccuracies indicate that predicting the weather is very complex. It does not indicate this historical data available is unreliable.
We live in a data-saturated world. The internet means that we have ready access to a plethora of secondary data. Not all of this data is reliable. It's not uncommon for data to be presented in a misleading manner to support a specific narrative that may not reflect the entire truth.
With so much data, we must ensure the data we choose to use is reliable. This idea is reflected in the Statistics content descriptors for Year 5 in the Australian Curriculum: Mathematics. Content descriptor AC9M5ST01 states that students need to “acquire, validate and represent data…”. Do you see it there? Students should not just acquire and represent data; they must also validate it.
How can you determine if secondary data is reliable and valid? The best approach is to use data from reputable sources. In this context, students are gathering climate data, and with various narratives emerging around climate issues, it’s essential to rely on information from trusted sources.
The Bureau of Meteorology records data from weather stations right across the country. The Bureau requires accurate data to make future predictions about the weather. We might joke that we cannot trust the Bureau because their weather predictions are not 100% accurate, but these inaccuracies indicate that predicting the weather is very complex. It does not indicate this historical data available is unreliable.