Answer:
Yes, we have sufficient evidence at the 0.02 level to support the company's claim.
Step-by-step explanation:
We are given that a sample of 1500 computer chips revealed that 32% of the chips do not fail in the first 1000 hours of their use. The company's promotional literature claimed that above 29% do not fail in the first 1000 hours of their use. 
Let Null Hypothesis,  : p
 : p  0.29  {means that less than or equal to 29% do not fail in the first 1000 hours of their use}
 0.29  {means that less than or equal to 29% do not fail in the first 1000 hours of their use}
Alternate Hypothesis,  : p > 0.29  {means that more than 29% do not fail in the first 1000 hours of their use}
 : p > 0.29  {means that more than 29% do not fail in the first 1000 hours of their use} 
The test statics that will be used here is One-sample proportions test;
           T.S. =  ~ N(0,1)
  ~ N(0,1)
where,  = proportion of chips that do not fail in the first 1000 hours of their use = 32%
 = proportion of chips that do not fail in the first 1000 hours of their use = 32%
             n = sample of chips = 1500
So, <u>test statistics</u> =  
 
                               = 2.491
<em>Now, at 0.02 level of significance the z table gives critical value of 2.054. Since our test statistics is more than the critical value of z so we have sufficient evidence to reject null hypothesis as it fall in the rejection region.</em>
Therefore, we conclude that more than 29% do not fail in the first 1000 hours of their use which means we have sufficient evidence at the 0.02 level to support the company's claim.