A computer company wants to determine if there is difference in the proportions of defective computer chips in a day's production from two different production plants, A and B. A quality control specialist takes a random sample of 100 chips from the day's production from plant A, and determines that there are 12 defective chips. The specialist then takes a random sample of 100 chips from the day's production from plant B, and determines that there are 10 defective chips. Based on the 90% confidence interval, (-0.05, 0.09), is there convincing evidence of a difference in the true proportions of defective chips from a day's production between the two plants? There is convincing evidence because the sample proportions of defective chips for the two plants are different. There is not convincing evidence because the interval contains 0. There is convincing evidence because the difference in the two sample proportions is 0.02. Since this is not 0, there is a difference in the true proportions of defective chips for the two plants. There is not convincing evidence because the interval contains both negative and positive values