A phone line carrier conducted a survey with their customers to verify their satisfaction with their coverage. Text messages were sent to random customers, asking questions such as: how good the coverage is where they live and they were asked to reply with a number from 1 to 5. The main question was how satisfied with the coverage are the customers and which states have the best and worst results? The population is composed by random customers of the carrier. Some variables to be observed are which plan the customer has, what phone, what area does he/she live (rural, urban). There are 500.000 individuals included in the dataset, divided by state, so 10.000 in each state randomly selected for the research and text messages were sent to different customers until all the numbers for the research were fulfilled.

For some data, we know the range R of the data is 12 and its median is 6. Find Estimated Lowest Number, and Estimated Highest Number for this data. Give you answers in the same order asked.

Here is an example from John and Jenn. When we return exams in our classes, we find it beneficial to share with students information on the distribution of scores. We provide this information so that students will have an idea of how they scored on the exam in comparison to their peers. However, deciding which descriptive information to provide to the class is not always an easy decision. These are modified grades from one of Jenn’s statistics classes. For this data set, the mean is 77, the mode is 92, and the median is 86. If you were the professor of the class, do you think sharing the mean scores on the exam with the class is a representative score of the data set? Why or why not? 9 or 11. The researchers predicted that the more a mother weighed during pregnancy, the higher the fat mass would be in the child. Such findings would support the developmental over nutrition hypothesis, which states that overeating during key developmental times has an influence on the offspring. The…

Levi-Strauss Co manufactures clothing. The quality control department measures weekly values of different suppliers for the percentage difference of waste between the layout on the computer and the actual waste when the clothing is made (called run-up). The data is in the table, and there are some negative values because sometimes the supplier is able to layout the pattern better than the computer. Do the data show that there is a difference between some of the suppliers? Test at the 1% level. Run-ups for Different Plants Making Levi Strauss Clothing Difference Plant Plant 1 11.9 Plant 1 3.9 -10.6 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 1 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 2 Plant 3 Plant 3 Plant 3 Plant 3 Plant 3 Plant 3 Plant 3…