A sample of 1700 computer chips revealed that $44 \%$ of the chips fail in the first 1000 hours of their use. The company's promotional literature states that $47 \%$ of the chips fail in the first 1000 hours of their use. The quality control manager wants to test the claim that the actual percentage that fail is different from the stated percentage. Make the decision to reject or fali to reject the null hypothesis at the 0.02 level. Answer Tables Keypad Keyboard Shortcuts Reject Null Hypothesis Fail to Reject Null Hypothesis

Step 1 ：The null hypothesis in this case is that the actual failure rate is 47%, as stated in the company's promotional literature. The alternative hypothesis is that the actual failure rate is not 47%.

Step 2 ：We are given a sample of 1700 chips, of which 44% fail in the first 1000 hours. We need to perform a hypothesis test to determine whether we should reject the null hypothesis or fail to reject it.

Step 3 ：We can use a z-test for proportions to perform this hypothesis test. The z-score is calculated as follows: \(z = (p_{hat} - p0) / \sqrt{(p0 * (1 - p0)) / n}\) where \(p_{hat}\) is the sample proportion, \(p0\) is the proportion under the null hypothesis, and \(n\) is the sample size.

Step 4 ：The critical z-score for a two-tailed test at the 0.02 level is approximately ±2.33. If the calculated z-score is greater than 2.33 or less than -2.33, we reject the null hypothesis. Otherwise, we fail to reject the null hypothesis.

Step 5 ：Let's calculate the z-score. We have \(n = 1700\), \(p_{hat} = 0.44\), \(p0 = 0.47\). The calculated z-score is -2.48, which is less than -2.33.

Step 6 ：Therefore, we reject the null hypothesis that the actual failure rate is 47%.

Step 7 ：Final Answer: \(\boxed{\text{Reject Null Hypothesis}}\)