Progress CheckUse this activity to assess whether you and your peers can: Calculate a 90% and a 95% confidence interval.Relate the interval width of a confidence interval to its margin of error (MOE).Compare interval widths of two confidence intervals and draw conclusions.Learn by DoingUse the rubric at the bottom of this page as a guide for completing this assignment.DirectionsSubmit your work:Commit a good-faith effort to address all items in the Prompt section below. Please be sure to number your responses.Complete your assigned peer reviews:After you submit your initial good-faith attempt, continue to the ANSWER(S) page and review your instructor's response. But please do not submit your corrected work yet.Within three days after the due date, return to this assignment and complete your assigned peer reviews (directions (Links to an external site.)).Submit your corrected work:We all learn from mistakes (our own and our classmates' mistakes). So please do not immediately correct your own mistakes. If possible, wait until you receive feedback from at least one of your peers. If necessary, correct your work and resubmit the entire assignment. Your instructor will only review and grade your most recent submission, so please do not refer to a previous submission.PromptHarris Interactive® conducted a poll of American adults in August of 2011 to study the use of online medical information. Of the 1,019 randomly chosen adults, 60% had used the Internet within the past month to obtain medical information. Use the results of this survey to create an approximate 95% confidence interval estimate for the percentage of all American adults who have used the Internet to obtain medical information in the past month.Calculate the 90% confidence interval.Which confidence interval has the smaller margin of error? Why does this make sense? Which confidence interval is more likely to contain the true percentage of all American adults who have used the Internet to obtain medical information in the past month? Why do you think so?RubricPeer Reviewed AssignmentPeer Reviewed AssignmentCriteriaRatingsPtsThis criterion is linked to a Learning OutcomeAddressing the Prompt8 ptsFull MarksAll parts of the Prompt are addressed. Answers are correct. Statistical vocabulary is used appropriately. Writing is clear and thought process is easy to follow.5 ptsPartial CreditSome parts of the prompt are not addressed, are incorrect, or are unclear.0 ptsNo MarksThe prompt is not addressed.8 ptsThis criterion is linked to a Learning OutcomeIndividual Penalty0 ptsNo individual penalty-1 ptsIndividual penalty.Please see the instructor comments for more information.0 ptsThis criterion is linked to a Learning OutcomePeer Reviews2 ptsFull MarksYou completed all assigned peer reviews (maximum of 2). For each peer review, the points you assigned in the rubric are appropriate. You included comments explaining the score you posted in the rubric. If you deducted points in the rubric, your comments explain what the author needs to do to earn a higher grade when the teacher grades the assignment.1 ptsPartial CreditCommitted a good-faith effort to provide a high-quality peer review, but many necessary instructive comments are missing.0 ptsNo MarksNo peer review provided or the comments are not instructive.2 ptsTotal Points: 10PreviousNext

You will find Video 4: Variation 1: Introduction and Quartiles by navigating to the MSL Tools for Success link under Course Home. The video begins at the park, with cyclists and joggers going by. We show a very slow old woman going by on a bike, and then a bunch of racing cyclists. We point out that sometimes, what is interesting about a data set is not its average but how much it varies. We then discuss the weather in New York and San Francisco, which have pretty much the same average annual temperature, even though New York has hot summers and cold winters. Quartiles as a measure of variation are introduced by way of the price of food on take-out menus. The video ends with a practical application in medical research, where mean exposure to a toxin is far less interesting than the fact that a small number of individuals are exposed to very high levels.Answer the follow questions separately 150-200 eachWhat are some examples, other than temperature, where similar averages can be associated with very different distributions? A few thoughts: costs (e.g., cost of illegally downloading a song online is the same average cost of driving above the speed limit, assuming that you are only caught speeding occasionally); ERA of pitchers (i.e., some are very consistent, others are sometimes brilliant, sometimes horrible); success rates in surgery (i.e., do we want an operation that most surgeons can do pretty well, or one in which a few surgeons are nearly perfect and some have very poor results?)Give some practical uses of knowing variation. A few thoughts: You are traveling to a job interview; what clothes do you need to pack for a trip? Doctors need to know distributions of blood values to know whether a patient is out of range; industrial engineers need to know distributions, for example the strength of a certain part to see if there is a problem with a manufacturing machine; clothing manufacturers need to know the distribution of sizes, for example children’s clothes for a certain age.For many years, the New York subway had no air conditioning on the grounds that the average trip was only 15 minutes, and 15 minutes without air conditioning is no hardship, even in the New York summer. Critique this reasoning.