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Daily Math Minute

Statistics Foundations

Understanding Probability

Probability as a number between 0 (impossible) and 1 (certain).

Intermediate15 min lesson3 min readUpdated August 12, 2026Author not yet attributed

A Number Between Impossible and Certain

Before reading on, think about these three events and roughly rank how likely each one is: flipping a coin and getting heads, rolling a standard die and getting a 7, and the sun rising tomorrow. Two of these have clear, extreme answers — what number do you think should represent each one?

Definition — Probability

A number between 0 and 1 (or equivalently, 0% to 100%) describing how likely an event is to occur. A probability of 0 means the event is impossible; a probability of 1 means it's certain.

Rolling a 7 on a standard six-sided die is impossible — a probability of 0. The sun rising tomorrow is, for all practical purposes, certain — a probability of 1. Every other event falls somewhere between those two extremes, and the closer to 1, the more likely the event. A fair coin landing heads sits exactly in the middle, at 1/2, since it's genuinely just as likely as not.

For an event where every outcome is equally likely, probability is found the same way you've calculated fractions all along: the number of outcomes that count as a 'success,' divided by the total number of possible outcomes.

Worked Example — Finding the Probability of a Simple Event

What is the probability of rolling an even number on a standard six-sided die? The even outcomes are 2, 4, and 6 — 3 favorable outcomes out of 6 total. The probability is 3/6, which simplifies to 1/2.

Worked Example — Finding the Probability of a Compound Condition

A bag contains 5 red marbles, 3 blue marbles, and 2 green marbles. What is the probability of drawing a marble that isn't red? There are 10 marbles total, and 5 of them aren't red (3 blue + 2 green). The probability is 5/10, which simplifies to 1/2.

Probability Simulator

Experiment

Run a trial to see the outcome here.

Simulation
0 / 200 trials

Histogram — experimental vs theoretical

Running probability — Law of Large Numbers

x = 100, y = 0.1667
Statistics

Mean

experimental

3.5 theoretical

Variance

experimental

2.917 theoretical

Standard deviation

experimental

1.708 theoretical

Trials

0 experimental

theoretical

Frequency table

OutcomeCountExperimentalTheoretical
100.167
200.167
300.167
400.167
500.167
600.167
Central Limit Theorem

Draws 300 independent samples of 5trials each from the current experiment, averages each sample, and histograms the resulting sample means — the distribution should look progressively more bell-shaped (normal) as the sample size grows, even though the experiment’s own distribution usually isn’t.

Tip

Check that a calculated probability always lands between 0 and 1 — a fraction greater than 1 or a negative value signals a setup mistake, since no probability can ever fall outside that range.

Common Mistakes

  • Writing a probability as a number greater than 1, such as reporting a fraction where the numerator exceeds the denominator.

    The number of favorable outcomes can never exceed the total number of possible outcomes — recheck the count of favorable outcomes if the resulting fraction is improper.

  • Miscounting the total number of possible outcomes, especially forgetting to include every category in a mixed group.

    Carefully add up every possible outcome in the entire situation before dividing — for the marble example, all 10 marbles count toward the total, not just the ones being asked about.

Key Takeaways

  • Probability is a number from 0 (impossible) to 1 (certain) describing how likely an event is.
  • For equally likely outcomes, probability equals the number of favorable outcomes divided by the total number of possible outcomes.
  • A valid probability always falls between 0 and 1, inclusive.

Summary

Understanding probability as a calculated fraction between 0 and 1 sets up the final lesson's comparison — what actually happens when an experiment is run, versus what theory predicts.