M4ML Lesson 5: Changes and Choices

This blog shows lesson plan to teach how probability helps us make smart gueses, and how machines do too.

The Coin Flip Challenge

Imagine you’re playing a game with your friend. You flip a coin ten times — if it lands on heads more than five times, you win!

You start flipping:
H, T, H, H, T, T, H, H, T, H

That’s six heads — you win!

But could you have known that before flipping? Nope! You could only guess the chance of winning.
That’s what probability is all about: measuring how likely something is to happen.

What Is Probability?

Probability is the math of possibility. It’s written as:

Probability = number of ways something can happen ÷ total number of possible outcomes

If you flip a coin, there’s one way to get heads, and two possible outcomes (heads or tails).
That means the chance of getting heads is 1 out of 2 — or 50%.

The Dice Challenge

Roll a die and try to predict what will come up next. Each side has a one-in-six chance.
If you roll it six times, you might not see every number — but if you roll it sixty times, you’ll start noticing a pattern: each number shows up about the same number of times.

This is called the Law of Large Numbers — the more times you try, the more the results start to “even out.”

The Probability Spinner

Draw a big circle and divide it like a pizza: maybe three green slices, one red, and two blue. Use a paperclip and pencil to make a spinner.

Now ask: what’s the chance it lands on blue?
There are two blue slices out of six total, so the probability is 2 out of 6 — about 33%.

Change the slices and spin again — you’ve just built your own probability experiment!

Thinking Like a Data Scientist

Probability helps us make choices when we can’t be certain. Humans do this every day.
We think: “What’s the chance it rains today?” or “Should I guess A or B on this test?” or “Will my friend text me back soon?”

Machines do the same thing — they just use math instead of feelings.

How This Connects to Machine Learning

Machine learning is full of probability. Computers constantly make smart guesses based on data.

A spam filter predicts: “This message is 90% likely to be spam.”
A weather app says: “There’s a 70% chance of rain.”
A voice assistant thinks: “You probably said ‘play music.’”

All of those are probability decisions. Machines don’t know for sure — they calculate what’s most likely.

Takeaway Message

Probability turns guessing into smart guessing.
It’s how both humans and machines deal with the unknown — and it’s one of the most powerful ideas in math and machine learning.

Optional Extensions

• Checkout M4ML Lesson 5 Google Colab notebook

• If you want to go further, try building a probability chart in Google Sheets,
• Roll two dice together to explore combined outcomes, or
• Talk about how weather forecasts or sports predictions rely on the same ideas you just learned.