Sugary cookie company has two different manufacturing plants. company officials want to test whether each plant fills the bags with the same number of ounces. a random sample of cookie bags from plant a had a mean of 24.7 ounces in each bag. a random sample from plant b had a mean of 22.2 ounces. they randomized the data over 100 trials, and the difference of means for each trial is shown in the dot plot below. what can sugary cookie company conclude from this study? a dot plot with the values of negative 2.5, negative 2.0, negative 1.5, negative 1.0, negative 0.5, 0.0, 0.5, 1.0, 1.5, 2.0, and 2.5 with frequencies of 3, 6, 9, 12, 0, 9, 8, 5, 1, 0, and 5 respectively.

This seems to indicate that the most probable mean difference for the weight of the cookie bags is -1. Then bags of cookies from plant A are usually 1 ounce heavier than those from plant B

Step-by-step explanation:

The plot of points for the 100 trials shows the frequency of occurrence of 11 possible values for the difference of average weight in ounces of the cookie bags:

 -2.5, -2.0, -1.5, -1.0, -0.5, 0.0, 0.5, 1.0, 1.5, 2.0 and 2.5.

If each of these values represents a possible 'event', then:

The points in the diagram show the number of times they were obtained in these values in the trial. In other words, these points show the frequency of occurrence. Therefore, the event that has fewer points in the diagram was the one that occurred less frequently during the tests, and that could lead to the conclusion that the least likely. On the other hand, the event with the most points is the one with the highest probability of occurrence.

In this experiment, the value for the mean difference that was most frequently obtained was -1 (with 12 points).

This seems to indicate that the most probable mean difference for the weight of the cookie bags is -1. Then bags of cookies from plant A are usually 1 ounce heavier than those from plant B

35 is an outlier

step-by-step explanation: