Today, we will be exploring probability. Probability is defined as the likelihood of an event occurring.
Probabilities are usually expressed in the form of a fraction following this format:
What you want to occur
What could occur
For example: What is the probability of randomly drawing a king of diamonds from a deck of cards.
There are 52 cards in the deck and none of the cards are alike, so 52 different outcomes are possible.
There is only one king of diamonds in the deck. So, there is only a 1 out of 52 chance of drawing a king
of diamonds when you draw one card randomly from the deck. We would express this as a fraction
1/52. This is called a theoretical probability, because in theory you would randomly draw a king of
diamonds once out of every 52 tries. There is also an experimental probability which is actually doing an
experiment to see how many times that event occurs out of the total number of tries. This probability is
also expressed as a fraction in the same format, for example, how many times would you draw the king
of diamonds out of 25 random draws, replacing the card each time.
Now that you know about probability, let's do an experiment. Find a number cube. If you have dice in a
game at home, use one of them. Choose a number 1-6. Now your experiment is to see how many times
you roll this number out of 25 tries. You will roll the dice 25 times and record how many times your
chosen number was rolled.
1. What is the number you chose?
2. How many times was this number rolled?
3. What is your experimental probability?
4. What is the theoretical probability of rolling that number?__
5. How close was your experimental probability to the theoretical?
6. What would happen if you increased the number of rolls to 50?
7. Using your experimental probability, how many times would you roll your number out of 100 tries?
8. Using the theoretical probability, how many times would you roll your number out of 100 tries?
In your own words, explain why your experimental probability was or was not the same as the
theoretical probability.