To answer both questions, we need to clarify the context. I assume you're referring to a machine (e.g., a random number generator or a dice) that produces a set of results. Here’s how we can approach each part:

1. Compute the Experimental Probability of Getting an Even Number:

The experimental probability is calculated based on actual results from the experiment. The formula for the experimental probability is:

$P(\text{even}) = \frac{\text{Number of even results}}{\text{Total number of results}}$

To compute this, I would need the following details:

• The total number of results obtained from the experiment.
• The number of even numbers observed in those results.

2. Compute the Theoretical Probability of Getting an Even Number (Assuming the Machine is Fair):

For theoretical probability, we assume the machine is fair, meaning all outcomes are equally likely. The probability of getting an even number depends on the total number of possible outcomes.

If the machine generates integers within a known range (e.g., from 1 to 6 for a standard dice), the theoretical probability would be:

$P(\text{even}) = \frac{\text{Number of even outcomes}}{\text{Total number of outcomes}}$

For example, if it's a 6-sided dice (numbers 1–6):

• The even numbers are: 2, 4, 6 (3 even numbers).
• The total possible outcomes are: 6 (1, 2, 3, 4, 5, 6).

Thus, the theoretical probability would be:

$P(\text{even}) = \frac{3}{6} = \frac{1}{2}$

Please provide more information about the experimental results (e.g., list of numbers) if you have them.

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Would you like details on how to calculate this for a different range of numbers or experiment type?

Here are some questions related to probability:

1. How would the experimental probability change if more even numbers appeared in the results?
2. What factors could cause the experimental probability to differ from the theoretical