Your favorite breakfast cereal contains a fidget toy in each box. There are three different fidget toys in the complete collection (spinner, pop strip, squishy ball) and each toy has an equal chance of being in each box.

You want to figure out what the probability is that you will get more than one squishy ball if you buy four boxes of the cereal. Which experiment could be used to simulate this situation?

1 answer

To simulate the situation of buying four boxes of cereal and determining the probability of getting more than one squishy ball, you can set up a simple experiment using a random selection process. The goal is to represent the different fidget toys in each box: spinner, pop strip, and squishy ball.

Here’s one way to conduct the experiment:

  1. Define the Outcomes: Assign a numerical value or letter to each fidget toy:

    • Spinner = 1
    • Pop Strip = 2
    • Squishy Ball = 3
  2. Simulate the Purchase of Boxes:

    • Use a random number generator or draw from a bag containing three distinct items that represent the toys (for example, three balls: one labeled '1', one labeled '2', and one labeled '3'). You could also use dice: for example, roll a six-sided die where numbers 1-2 represent spinner, 3-4 represent pop strip, and 5-6 represent squishy ball.
  3. Draw Four Times:

    • Perform the random selection process four times to simulate buying four boxes of cereal. Each selection corresponds to one box.
  4. Count Squishy Balls:

    • After drawing or generating four outcomes, count how many times you got a '3' (squishy ball).
  5. Repeat the Experiment:

    • To find a good approximation of the probability, repeat the above process many times (e.g., 100 or more trials).
  6. Determine the Probability:

    • Record how many of the trials resulted in getting more than one squishy ball (i.e., 2, 3, or 4 squishy balls) out of the four selections.
    • Divide the number of trials that resulted in more than one squishy ball by the total number of trials to find the experimental probability.

This simulation thus allows you to approximate the probability of getting more than one squishy ball over multiple trials, which can help approximate the theoretical probability for the situation outlined.