Final answer:
The question involves using hypothesis testing to determine if there is evidence to support a company's claim about the non-failure rate of their computer chips. A sample of 900 chips showed a 69% non-failure rate compared to the claimed 65%. A formal hypothesis test comparing to a 0.01 significance level is required for a conclusive result.
Step-by-step explanation:
The question at hand pertains to determining whether there is sufficient evidence at the 0.01 significance level to support a company's claim that more than 65% of their computer chips do not fail within the first 1000 hours of use. A sample of 900 chips indicated a non-failure rate of 69%. To assess the claim, a hypothesis test can be conducted. The null hypothesis (H0) states that the non-failure rate is 65% or less, while the alternative hypothesis (H1) states that the non-failure rate is more than 65%. Since the observed sample proportion of 69% is higher than the claimed proportion of 65%, and the sample size is large, it may suggest evidence supporting the company's claim. However, without calculating the test statistic and comparing it to the critical value or p-value for significance level 0.01, we cannot make a conclusive decision.