Final answer:
To test the hypothesis, we would compare the sample proportion of defects to the hypothesized proportion using a test of proportions and calculate the p-value. If the p-value is lower than the significance level, the decision is to reject the null hypothesis. However, specific details needed for this are missing in the question.
Step-by-step explanation:
The student has been asked to test a hypothesis regarding the proportion of defective parts in manufacturing. Specifically, they are looking at whether their data supports the null hypothesis H0: p = 0.02, which claims that the true proportion of defects is 2%. Given that out of 500 parts, 10 are rejected, we can calculate the sample proportion of defects (p') and use a test of proportions to compare against the null hypothesis.
To test the hypothesis, we calculate the test statistic under the null hypothesis and derive the p-value from the test statistic. If the p-value is less than the chosen level of significance (alpha), usually 0.05 or 0.01, we reject the null hypothesis. The provided information suggests we would compare the sample proportion to the hypothesized proportion of 0.02. If this hypothetical test generated a p-value less than the alpha level, the conclusion would be to reject the null hypothesis. However, the question seems to be missing specific details to complete the test, such as the significance level to be used and the calculation of the test statistic itself.