Statistics - Maths of Real Life
This pilot collection of resources is designed to introduce key statistical ideas and help students to deepen their understanding.
Introduction
In the 21st century, more data is collected about us than ever before, and as computers become more powerful, we can process, interpret and analyse large data sets to look for patterns, make predictions, and discover new ideas. Whether you study mathematics, science, social sciences or
humanities, it is becoming increasingly important to have a good grasp of statistical ideas and an understanding of the maths underlying statistical methods.These resources are designed to introduce key statistical ideas needed for advanced study. They also give opportunities to consolidate your understanding by applying it to new and engaging contexts. Try the activities to delve into the concepts of hypothesis testing, sampling, and distributions, and explore some of the fascinating and complex issues surrounding the interpretation and representation of data. Scroll down to find articles which explain key ideas and go more deeply into the concepts.
To complement each resource, there are Teachers' Resources with suggestions for how the tasks can be used in the classroom.
Statistical Shorts
Can you decide whether these short statistical statements are always, sometimes or never true?
A Population Survey
A geographical survey: answer the tiny questionnaire and then analyse all the collected responses...
Which Spinners?
Can you work out which spinners were used to generate the frequency charts?
Counting Fish
I need a figure for the fish population in a lake. How does it help to catch and mark 40 fish?
Data Matching
Use your skill and judgement to match the sets of random data.
Where Are You Flying?
Where do people fly to from London? What is good and bad about these representations?
One Variable, Two Variable, Three Variable, More
Displaying one-variable and two-variable data can be straightforward; what about three or more?
Sleep: the Silent Killer
"Too much sleep is deadly" proclaimed the newspaper headline. Is this true?
Do You Brush Your Teeth Every Day?
How can we find out answers to questions like this if people often lie?
Stats Statements
Are these statistical statements sometimes, always or never true? Or it is impossible to say?
Hypothetical Shorts
Some short statements about hypothesis testing: are they true, false, or somewhere in between?
Robin's Hypothesis Testing
How many trials should we do in order to accept or reject our null hypothesis?
Powerful Hypothesis Testing
How effective are hypothesis tests at showing that our null hypothesis is wrong?
Can You Find ... Random Variable Edition
Can you create random variables satisfying certain conditions?
Binomial or Not?
Are these scenarios described by the binomial distribution?
Binomial Conditions
When is an experiment described by the binomial distribution? Why do we need both the condition about independence and the one about constant probability?
A Well-stirred Sample
Typical survey sample sizes are about 1000 people. Why is this?
Understanding Hypotheses
This article explores the process of making and testing hypotheses.
A Probability Conundrum
What do we mean by probability? This simple problem may challenge your ideas...
The Surveyor Who Came to Tea
This article discusses how a survey company carries out its surveys and some of the issues involved.
What Is a Random Variable, Really?
This article offers an advanced perspective on random variables for the interested reader.
What Is a Hypothesis Test?
This article explores the meaning of hypothesis tests, and also some of the major difficulties in interpreting them
Challenging Data Tasks: The Making of "Where Are You Flying?"
How was the data for this problem compiled? A guided tour through the process.
You may also like
Over-booking
The probability that a passenger books a flight and does not turn up is 0.05. For an aeroplane with 400 seats how many tickets can be sold so that only 1% of flights are over-booked?
Binomial Conditions
When is an experiment described by the binomial distribution? Why do we need both the condition about independence and the one about constant probability?