In the process of solving a problem, you determine what the problem is, collect an amount of data that someone thinks is sufficient to answer the questions, and begin your analysis. Once you've completed your testing and either supported or rejected your hypothesis, the next question is, now what? It is tempting to take your results at face value: In conclusion, reject the null hypothesis in support of the alternative hypothesis. There is a significant disparity in defect percentages between Model 1 and the other two models. Accept test for Model 1 vs. Model 2 and Model 1 vs. Model 3, suggesting a condition for corrective measures on Model 1. These corrective measures could include [specific actions such as adjusting the manufacturing process, improving quality control, or enhancing product design]. Reject the Model 2 vs. Model 3 test. It indicates equivalent performance between these two models concerning defect percentages. Based on the results, I recommend attentive analysis and corrective measures on Model 1 to comprehend and ease the increased defect percentage. Conducted to pinpoint the exact causes of defects, further investigation into the manufacturing process of Model 1 should be. Implement continuous monitoring and quality control measures to ensure practical