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{{T}}
[[Category:English]]
[[Category:Probability and Simple Experiments]]

{{BR}}
= Introduction =

Probability is a way to describe '''chance'''. It helps you answer questions such as: How likely is a coin to land on heads? Which numbers can appear when you roll a die? Is an event impossible, unlikely, likely, or certain?

In this aiMOOC, you will learn probability through simple experiments with coins, dice, spinners, and counters. You will make predictions, collect data, compare results, and explain why a short experiment may not look exactly like the mathematical prediction.

{{#ev:youtube|https://www.youtube.com/watch?v=7XuNVVlD98g|500|center}}

{{BR}}
== What You Will Learn ==

By the end of the course, you should be able to explain [[English:Probability|probability]] in everyday language, identify outcomes and events, list a simple [[English:Sample space|sample space]], find probabilities when outcomes are equally likely, run a fair chance experiment, record results with tallies or tables, and compare theoretical probability with experimental probability.

{{BR}}
= The Language of Chance =

Probability can be shown on a scale from '''0 to 1'''. In the simple finite experiments in this course, a probability of 0 means an event is impossible and a probability of 1 means it is certain. A probability of one half lies in the middle and describes an even chance.

[[File:Scaleprob.png|500px|frameless|center]]

You can also use words. '''Impossible''' means the event cannot happen in the stated experiment. '''Unlikely''' means it can happen but has a small chance. '''Even chance''' means it is just as likely to happen as not happen. '''Likely''' means it has a large chance. '''Certain''' means it must happen in the stated experiment.

Probabilities can be written as fractions, decimals, or percentages. For example, one half, 0.5, and 50% describe the same probability.

{{#ev:youtube|https://www.youtube.com/watch?v=KzfWUEJjG18|500|center}}

{{BR}}
= Experiments, Outcomes, Events, and Sample Spaces =

A '''chance experiment''' is an activity whose result is not known before it happens. Tossing a coin, rolling a die, or drawing a counter from a bag are simple examples.

An '''outcome''' is one possible result. When you toss a coin, "heads" is an outcome. An '''event''' is an outcome or a group of outcomes that you are interested in. When you roll a die, "rolling an even number" is an event because it includes more than one outcome.

The '''sample space''' is the complete set of possible outcomes. For one toss of a coin, the sample space is heads and tails. For one roll of a standard six-sided die, the sample space is 1, 2, 3, 4, 5, and 6.

[[File:Coin Toss (3635981474).jpg|500px|frameless|center]]

{{BR}}
== Equally Likely Outcomes ==

Outcomes are '''equally likely''' when each has the same chance. A fair coin has two equally likely sides. A fair six-sided die has six equally likely faces.

For equally likely outcomes, you can find a simple theoretical probability with:

'''Probability of an event = favorable outcomes ÷ total possible outcomes'''

For a fair coin, the probability of heads is 1 out of 2, or one half. For a fair die, the event "roll an even number" has three favorable outcomes: 2, 4, and 6. There are six outcomes altogether, so the probability is 3 out of 6, which simplifies to one half.

[[File:Dice - 1-2-4-5-6.jpg|500px|frameless|center]]

{{BR}}
= Theoretical Probability =

'''Theoretical probability''' is the probability you calculate from the structure of a fair experiment before you collect results. It tells you what chance the model predicts.

Suppose a bag contains four counters: three red and one blue. If the counters are mixed well and each counter is equally likely to be drawn, the theoretical probability of drawing red is three quarters. The theoretical probability of drawing blue is one quarter.

Theoretical probability does not promise what will happen on the next trial. A fair coin can land on heads several times in a row. Probability describes long-run chance, not a fixed pattern that every short set of trials must follow.

{{BR}}
== Expected Results Are Predictions, Not Guarantees ==

If the probability of rolling a 6 is one sixth, then in 60 rolls you might expect about 10 sixes because one sixth of 60 is 10. You could get 8, 10, 12, or another number. The expected count is a useful prediction, not a guarantee.

{{BR}}
= Experimental Probability =

'''Experimental probability''' comes from results you actually observe. It is also called relative frequency.

'''Experimental probability of an event = number of times the event happens ÷ total number of trials'''

Imagine that you roll a die 20 times and record these results:

{| class="wikitable" align="center"
! Die face
! Frequency
|-
| 1 || 4
|-
| 2 || 2
|-
| 3 || 5
|-
| 4 || 3
|-
| 5 || 1
|-
| 6 || 5
|}

The even results are 2, 4, and 6. They appeared 2 + 3 + 5 = 10 times. The experimental probability of an even number is therefore 10 out of 20, or one half. In this particular example, the experimental result matches the theoretical probability exactly, but that does not happen every time.

{{#ev:youtube|https://www.youtube.com/watch?v=YP6y9KstyMM|500|center}}

{{BR}}
== Why Repeat an Experiment Many Times? ==

Short experiments can be bumpy. Five coin tosses could give four heads and one tail even when the coin is fair. When you repeat a fair chance experiment many times, the experimental proportion often becomes more stable and tends to move closer to the theoretical probability, although it does not have to equal it exactly.

{{#ev:youtube|https://www.youtube.com/watch?v=Nos-xOCpQqg|500|center}}

{{BR}}
= Designing a Simple Probability Experiment =

A good experiment is clear enough that another learner could repeat it in the same way. Decide what you will test, list the possible outcomes, predict the theoretical probability if you can, choose a number of trials, keep the method the same, and record every result.

Use safe classroom materials. For a coin experiment, toss the coin onto a clear table rather than toward people. For a die experiment, roll inside a tray or box lid so the die does not roll away. For a counter experiment, mix the counters well before each draw.

If you draw a counter and then put it back before the next draw, the contents of the bag stay the same from trial to trial. If you do not replace it, the contents change, so the probability for the next draw may also change.

{{BR}}
== Recording Results Clearly ==

A tally chart helps you count outcomes without relying on memory.

{| class="wikitable" align="center"
! Outcome
! Tally
! Frequency
|-
| Heads || ||
|-
| Tails || ||
|}

Before the experiment, write a prediction. After the experiment, calculate experimental probability and compare it with the theoretical probability. Then explain any difference using evidence from your results.

{{BR}}
= More Than One Trial =

When an experiment is repeated, the sample space grows. For example, three coin tosses can produce sequences such as heads-heads-tails or tails-heads-heads. A tree diagram is one way to organize all possible sequences.

[[File:Three fair coin flips tree diagram.svg|500px|frameless|center]]

For Grades 5–6, the most important idea is not multiplying several probabilities. Focus first on listing outcomes carefully and noticing that repeated random trials can create many possible sequences.

{{BR}}
= Fairness and Randomness =

A '''fair''' device gives the intended outcomes equal chances. A balanced six-sided die is designed so that each face has the same theoretical probability. A spinner with unequal sections does not give each color the same chance unless the sections have equal size.

'''Random''' does not mean "without rules." It means the next individual outcome is not known for sure in advance even though the possible outcomes and their probabilities may be understood.

You can investigate fairness by collecting data, but a small number of trials cannot prove that an object is perfectly fair or unfair. A strong investigation uses many trials, careful recording, and cautious conclusions.

{{BR}}
= Probability in Everyday Life =

Probability helps people describe uncertainty in weather forecasts, games, science experiments, sports, quality checks, and many other situations. Good probability thinking asks: What are the possible outcomes? Are they equally likely? What evidence do I have? How many observations were made?

Probability is also connected to [[English:Fractions|fractions]], [[English:Decimals|decimals]], [[English:Percentages|percentages]], [[English:Data|data]], and [[English:Statistics|statistics]]. These links make probability useful far beyond games of chance.

{{BR}}
= Interactive Tasks =

{{BR}}
== Quiz: Test Your Knowledge ==

{{MC}}

'''What does probability describe?'''
(How likely an event is to happen)
(!How heavy an object is)
(!How long a ruler is)
(!How fast a number grows)

{{E}}
<br>

{{MC}}

'''What does a probability of zero mean?'''
(The event is impossible)
(!The event is certain)
(!The event has an even chance)
(!The event happened once)

{{E}}
<br>

{{MC}}

'''What is the probability of heads on one toss of a fair coin?'''
(One half)
(!One quarter)
(!Two thirds)
(!One whole)

{{E}}
<br>

{{MC}}

'''What is the probability of rolling an even number on a fair six-sided die?'''
(One half)
(!One sixth)
(!One third)
(!Five sixths)

{{E}}
<br>

{{MC}}

'''What is an outcome?'''
(One possible result of an experiment)
(!A list of every possible result)
(!A guarantee about the next trial)
(!A tool for measuring length)

{{E}}
<br>

{{MC}}

'''What is the sample space for one coin toss?'''
(Heads and tails)
(!Heads only)
(!Tails only)
(!One two three four)

{{E}}
<br>

{{MC}}

'''A coin is tossed twelve times and lands on heads seven times. What is the experimental probability of heads?'''
(Seven twelfths)
(!Five twelfths)
(!One half exactly)
(!Seven fifths)

{{E}}
<br>

{{MC}}

'''Why is it useful to repeat a probability experiment many times?'''
(To get a more stable experimental estimate)
(!To make every outcome appear equally often)
(!To guarantee the theoretical answer)
(!To remove the need to record data)

{{E}}
<br>

{{MC}}

'''A bag has three red counters and one blue counter. Each counter is equally likely to be drawn. What is the theoretical probability of red?'''
(Three quarters)
(!One quarter)
(!One half)
(!Four thirds)

{{E}}
<br>

{{MC}}

'''What is the main difference between theoretical and experimental probability?'''
(Theoretical is calculated from a model while experimental uses observed results)
(!Theoretical uses only pictures while experimental uses only words)
(!Theoretical is always larger than experimental)
(!Experimental probability never changes)

{{E}}
<br>

{{BR}}
== Memory Game ==

<div class="memo-quiz">
{|
|-
| Probability || A measure of how likely an event is
|-
| Outcome || One possible result of a chance experiment
|-
| Experiment || A repeatable activity with an uncertain result
|-
| Event || An outcome or group of outcomes you are interested in
|-
| Sample space || The complete set of possible outcomes
|-
| Theoretical probability || A chance calculated from a model of the experiment
|-
| Experimental probability || A chance estimated from results that were observed
|}
{{E}}
<br>

{{BR}}
== Drag and Drop ==

<div class="lueckentext-quiz">

{| class="wikitable"
! Match the correct terms.
! Topic
|-
| '''Certain'''
| Drawing a red counter from a bag that contains only red counters
|-
| '''Likely'''
| Drawing a red counter from a bag that contains mostly red counters and one blue counter
|-
| '''Even chance'''
| Getting heads when tossing a fair coin
|-
| '''Unlikely'''
| Drawing a blue counter from a bag that contains mostly red counters and one blue counter
|-
| '''Impossible'''
| Rolling a seven with a standard six-sided die
|}
{{E}}

<br>
...
<br />

{{BR}}
== Crossword Puzzle ==

<div class="kreuzwort-quiz">
{|
|-
| Chance || What word describes the possibility that something may happen?
|-
| Outcome || What is one possible result of an experiment called?
|-
| Experiment || What do you call a repeatable activity used to collect probability results?
|-
| Event || What is an outcome or group of outcomes that you are interested in?
|-
| Random || What word describes a result that cannot be known for sure before the trial?
|-
| Frequency || What word means the number of times an outcome occurs?
|}
{{E}}
<br>

{{BR}}
== LearningApps ==

<iframe> https://learningapps.org/index.php?s=Probability+and+Simple+Experiments </iframe>

{{BR}}
== Cloze Text ==

<quiz display=simple>
{'''Complete the text.'''<br>
|type="{}"}
Probability describes how { likely } an event is to happen. A result that cannot happen has probability { zero }. One possible result of an experiment is called an { outcome }. The full set of possible results is the { sample space }. For equally likely outcomes, theoretical probability compares favorable outcomes with the { total } number of possible outcomes. Experimental probability is based on results that were actually { observed }. Repeating an experiment many times usually makes the experimental proportion more { stable }. A fair coin has a theoretical probability of { one half } for heads.
</quiz>

<br>

{{BR}}
= Open-Ended Tasks =

{{BR}}
=== Easy ===
# [[English:Coin Toss Journal|Coin Toss Journal]]: Toss a coin 20 times, record each result, calculate the experimental probability of heads, and write two sentences comparing your result with one half.
# [[English:Probability Scale Poster|Probability Scale Poster]]: Make a poster from impossible to certain and add at least five everyday or classroom events in sensible positions on the scale.
# [[English:Dice Outcome Chart|Dice Outcome Chart]]: Roll a fair six-sided die 30 times, make a tally chart for all six outcomes, and identify the most and least frequent results in your experiment.
# [[English:Spinner Design|Spinner Design]]: Draw a four-section spinner with equal sections, label the sections with four colors, and explain the theoretical probability of landing on each color.

{{BR}}
=== Standard ===
# [[English:Counter Bag Investigation|Counter Bag Investigation]]: Create a bag with counters of two or three colors, predict the probability of each color, draw with replacement at least 40 times, and compare your observed frequencies with your predictions.
# [[English:Chance Language Interview|Chance Language Interview]]: Interview three people about how they use words such as likely, unlikely, and certain, then write a short report about where their everyday language agrees with mathematical probability and where it may be less exact.
# [[English:Probability Game Design|Probability Game Design]]: Invent a simple game using a coin, die, spinner, or counters, write the rules, calculate the main probabilities, and test whether the game feels fair.
# [[English:Experiment Video Report|Experiment Video Report]]: Record a short video showing a safe probability experiment, your data table, your calculation of experimental probability, and your explanation of the result.

{{BR}}
=== Advanced ===
# [[English:Fairness Investigation|Fairness Investigation]]: Test a coin, die, or homemade spinner for possible bias using at least 100 trials, graph the data, and explain why your evidence can suggest unfairness but cannot prove it with certainty.
# [[English:Small and Large Samples|Small and Large Samples]]: Compare the experimental probability from the first 10 trials of an experiment with the result after at least 100 trials, then explain what changed and why.
# [[English:Expected and Observed Results|Expected and Observed Results]]: Choose an event with a known theoretical probability, predict the expected count for a large number of trials, perform or simulate the trials, and analyze the difference between expected and observed counts.
# [[English:Probability in the Community|Probability in the Community]]: Visit a science museum, school fair, sports club, or other suitable place where chance or data is used, document one example with notes or a photo if permitted, and explain the probability ideas you notice.

{{:Open Task - Create a MOOC}}

{{BR}}
= Learning Assessment =

# [[English:Reasoning with a Bag Model|Reasoning with a Bag Model]]: A bag has several colors of counters; explain how changing the number of one color changes its theoretical probability and justify your answer with fractions.
# [[English:Compare Prediction and Data|Compare Prediction and Data]]: Given a theoretical probability and a table of experimental results, decide whether the data are reasonably consistent with the model and support your conclusion with evidence.
# [[English:Design a Fair Test|Design a Fair Test]]: Plan a chance experiment that another learner can repeat, including the sample space, number of trials, recording method, and steps that make the test fair.
# [[English:Find and Fix an Error|Find and Fix an Error]]: Analyze a fictional learner's claim that a fair coin must alternate heads and tails, explain the error, and replace it with an accurate probability statement.
# [[English:Transfer to a New Situation|Transfer to a New Situation]]: Use probability ideas to analyze a new game, spinner, weather statement, or classroom scenario and explain which information is needed before a probability can be calculated.
# [[English:Communicate Results|Communicate Results]]: Present one experiment using a table or graph and write a clear conclusion that distinguishes what the data show from what the theoretical model predicts.

<br>
<br>

{{BR}}
= Evidence of Learning =

'''Knowledge:''' You can define probability, outcome, event, sample space, theoretical probability, and experimental probability in your own words, and you can connect simple probabilities to fractions, decimals, percentages, and chance language.

'''Skills:''' You can list outcomes, identify favorable outcomes, calculate simple probabilities for equally likely outcomes, run repeated trials, record frequencies, calculate experimental probabilities, and compare observed results with a prediction.

'''Products:''' Strong evidence may include a completed data table, a probability scale, a graph, a written experiment report, a designed game or spinner, a short presentation, or a video explanation.

'''Reasoning:''' You can explain why random results do not need to follow a fixed pattern, why a small sample can differ from the theoretical probability, and why more trials can provide a more stable estimate.

'''Transfer:''' You can recognize and explain probability ideas in unfamiliar games, classroom decisions, simple scientific investigations, weather statements, sports data, or other everyday situations.

<br>
<br>

{{BR}}
= OERs on the Topic =

The English Wikipedia article below offers a broader reference on [[English:Probability|probability]]. Some sections go beyond Grades 5–6, so use it mainly to explore definitions, examples, and images with teacher guidance when needed.

<iframe> https://en.m.wikipedia.org/wiki/Probability </iframe>

<br>

{{BR}}
= Linked Learning Areas =

{| align=center
{{:D-Tab}}
'''[[English:Probability and Simple Experiments|Probability and Simple Experiments]]'''
# [[English:Probability|Probability]]
# [[English:Fractions|Fractions]]
# [[English:Decimals|Decimals]]
# [[English:Percentages|Percentages]]
# [[English:Data|Data]]
# [[English:Statistics|Statistics]]
# [[English:Sample space|Sample space]]
# [[English:Experimental probability|Experimental probability]]
# [[English:Randomness|Randomness]]
|}

{{BR}}
= aiMOOC Projects =
[[Category:English]]
[[Category:Probability and Simple Experiments]]
[[Category:Mathematics]]
[[Category:Probability]]
[[Category:Statistics]]
[[Category:Grades 5-6]]
[[Category:AI_MOOC]]
[[Category:GPT aiMOOC]]
{{MT}}

English:Probability and Simple Experiments - Versionsgeschichte

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