Data Science for Young Minds — Grade 3
| Topic | Details |
|---|---|
| Theoretical probability | Theoretical probability: calculated from math, not experiments |
| Why a fair coin should land heads 50% of | Why a fair coin should land heads 50% of the time — in theory |
| Calculating theoretical probability for | Calculating theoretical probability for dice, spinners, and cards |
| The key word | The key word: 'should' — theory predicts the ideal, not the actual |
| Experimental probability | Experimental probability: calculated from actual experiment results |
| How to calculate | How to calculate: number of times it happened / total trials |
| Why experimental results rarely match th | Why experimental results rarely match theoretical exactly |
| Activity | Activity: flip a coin 50 times and calculate experimental probability of heads |
| What the law of large numbers says | What the law of large numbers says: more trials = closer to theory |
| 10 flips vs 100 flips vs 1000 flips | 10 flips vs 100 flips vs 1000 flips: watching convergence |
| Why this matters | Why this matters: small samples are unreliable |
| Activity | Activity: flip a coin 10, 50, and 100 times — graph how the percentage changes |
| Small sample illusions | Small sample illusions: patterns that are not real |
| The hot hand fallacy in sports | The hot hand fallacy in sports |
| Why medical studies need thousands of pa | Why medical studies need thousands of participants |
| How to recognize when a sample is too sm | How to recognize when a sample is too small to trust |
Calculate what should happen based on math alone — before running any experiment.
Run experiments and see how results compare to theoretical predictions.
The more you repeat an experiment, the closer results get to the theoretical prediction. This is one of the most powerful ideas in probability.
Small groups of data can show dramatic patterns that disappear with more data. Learn why this matters for real-world decisions.