### There are 18 results

Broad Topics >

Handling, Processing and Representing Data > Interpreting data

##### Age 14 to 16 Challenge Level:

Match the cumulative frequency curves with their corresponding box plots.

##### Age 14 to 16 Challenge Level:

Is it the fastest swimmer, the fastest runner or the fastest cyclist who wins the Olympic Triathlon?

##### Age 14 to 18 Challenge Level:

How can we find out answers to questions like this if people often lie?

##### Age 16 to 18 Challenge Level:

"Too much sleep is deadly" proclaimed the newspaper headline. Is this true?

##### Age 14 to 18 Challenge Level:

A geographical survey: answer the tiny questionnaire and then analyse all the collected responses...

##### Age 14 to 18 Challenge Level:

Displaying one-variable and two-variable data can be straightforward; what about three or more?

##### Age 16 to 18

How was the data for this problem compiled? A guided tour through the process.

##### Age 14 to 18 Challenge Level:

Where do people fly to from London? What is good and bad about these representations?

##### Age 14 to 18 Challenge Level:

This pilot collection of resources is designed to introduce key statistical ideas and help students to deepen their understanding.

##### Age 14 to 16 Challenge Level:

Are you at risk of being a victim of crime? How does your perception of that risk compare with the facts and figures?

##### Age 11 to 16 Challenge Level:

How risky is your journey to school?

##### Age 11 to 16 Challenge Level:

Simple models which help us to investigate how epidemics grow and die out.

##### Age 11 to 16 Challenge Level:

Can you make sense of the charts and diagrams that are created and used by sports competitors, trainers and statisticians?

##### Age 11 to 16 Challenge Level:

Can you make sense of the charts and diagrams that are created and used by sports competitors, trainers and statisticians?

##### Age 14 to 18 Challenge Level:

Does weight confer an advantage to shot putters?

##### Age 14 to 18

This article explores the process of making and testing hypotheses.

##### Age 14 to 18 Challenge Level:

Use your skill and judgement to match the sets of random data.

##### Age 14 to 16 Challenge Level:

Can you make sense of information about trees in order to maximise the profits of a forestry company?