People who bought this also bought
An app tells you that people who bought a football also bought shin pads. Nobody typed that rule. A computer found it by looking at thousands of baskets.
Finding patterns and making careful guesses about the future is called predictive analytics. It also needs honest checking at the end.
By the end of this lesson
Note
I can use statistics, a simple model and a pattern search on data, then judge how well the result answers the need.
Key words
| Word | What it means |
|---|---|
| Predictive analytics | using past data to make a careful guess about what comes next |
| Statistics | numbers that summarise data, such as the average |
| Model | a simple rule built from data to make a prediction |
| Data mining | searching large data for patterns |
| Evaluate | to judge how well something worked |
The cells students fill in are left blank in this preview.
Starter: what you already know
Have a go
Starter: what you already know
4 questionsYour answers are marked here and are not kept. A college account keeps every student’s marks.
Statistics summarise a big table
First define the data: what each field means and what each row is. Then produce statistics. These are numbers that sum up the data: how many, the smallest, the biggest and the average.
The average (the total divided by how many) tells you the typical value. The biggest and smallest tell you the spread.
Try it: summarise six months
-- Whole-number statistics for web orders.
SELECT COUNT(*) AS months,
MIN(orders) AS smallest,
MAX(orders) AS biggest,
SUM(orders) / COUNT(*) AS average
FROM web_orders;
-- SUM divided by COUNT is the average, kept as a whole number.
Check
Have a go
Check
3 questionsYour answers are marked here and are not kept. A college account keeps every student’s marks.