Five bad rows, one shop
On Tuesday an analyst finds five bad rows in a sales sheet. Each looks different: "no date", "price blank", "name missing", "total zero", "date in the future".
A new analyst fixes them one by one. An experienced one sees that all five came from the same shop. One fix at the source may solve all of them.
By the end of this lesson
Note
I can find a pattern in data and use it to make a prediction.
Key words
| Word | What it means | Example |
|---|---|---|
| Pattern recognition | Spotting things that repeat or look alike | |
| Trend | A change that keeps going in one direction | sales rise each week |
| Similarity | A way two things are alike | |
| Common feature | Something that two problems share | |
| Prediction | A careful guess about what will happen next | |
| Assumption | Something you accept as true without proof |
The cells students fill in are left blank in this preview.
Starter
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Starter
3 questionsYour answers are marked here and are not kept. A college account keeps every student’s marks.
Pattern recognition saves time
The purpose of pattern recognition is to use what repeats. If you have seen a problem before, you already know a fix. If many problems share a cause, you fix the cause once.
A week of sales rows
| Day | Shop | Problem | Row |
|---|---|---|---|
| Monday | North | Price blank | Row 4 |
| Monday | North | Price blank | Row 9 |
| Tuesday | East | Date missing | Row 15 |
| Tuesday | North | Price blank | Row 21 |
| Wednesday | West | Name missing | Row 30 |
| Thursday | North | Price blank | Row 38 |
The cells students fill in are left blank in this preview.
Check
Have a go
Check
3 questionsYour answers are marked here and are not kept. A college account keeps every student’s marks.