To determine the percentage of defective watches that Acrotime expects to replace under its 2-year warranty, we need to know the probability or rate of defects over that period. If the company has data on the likelihood of watches becoming defective within 2 years, we can calculate an expected percentage.

Here's a general approach:

1. Let $p$ be the probability of a watch becoming defective within 2 years.
2. Multiply $p$ by 100% to get the expected percentage of watches replaced.

For example, if the probability of a defect within 2 years is 5%, then Acrotime would expect to replace: $5\% \text{ of their total production under warranty.}$

Could you provide the probability or percentage of defective watches within that timeframe?

Would you like more help, or do you have any additional details to add?

Here are some related questions for further exploration:

1. How can companies reduce the probability of product defects?
2. What is the impact of warranties on customer satisfaction and brand loyalty?
3. How do companies estimate defect rates for new products without historical data?
4. What are the costs involved in offering a warranty for 2 years versus a longer period?
5. How can statistical analysis help predict warranty replacement rates?

Tip: Having data on past defects can help improve product quality control and warranty planning.