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Unformatted text preview: Lecture Notes for Stat 1000 by Dr. Nancy Pfenning Note: Survey/article exercises must be handed in to me in lecture along with the textbook homework problems by the due date. They must be your own individual work. Each is worth a maximum of 2 points. For problems involving survey variables, access the survey data via my website email@example.com www.pitt.edu/ nancyp/stat-1000/index.html where there is a link to the most recent survey data at surveymm-dd-yy.txt followed by instructions for downloading into MINITAB. Be sure to choose different variables from those used in lecture examples. For problems involving your own newspaper articles or internet reports, you must hand in a copy of the article or report itself. Lecture 1 Chapter 1: Statistics Success Stories and Cautionary Tales Statistics is a collection of procedures and principles for gathering data and analyzing information in order to help people make decisions when faced with uncertainty. Some years ago, Rutgers football team managed to rack up seven turnovers from Pitts team, but Pitt won 29-17. Pitts coach Walt Harris remarked, The scoreboard is what matters. Statistics are for proverbial losers. Pitts team may have come out ahead in spite of the statistics involved, but studying statistics can actually put you ahead of the game in that it will help you understand the world around you much better than you would otherwise. Consider the following quotation: The country is hungry for information; everything of a statistical character, or even a statistical appearance, is taken up with an eagerness that is almost pathetic; the community have not yet learned to be half skeptical and critical enough in respect to such statements. If this was true back in the 1870s when spoken by General Francis A. Walker (superintendent of the 1870 census) how much more true is it today, when we are bombarded with information of a statistical nature in virtually all aspects of our lives? Here are some examples of questions which can be answered with the help of statistics: Example Suppose we have the following data on how much money three students earned (in thousands of dollars) last year: Name Earned Jessica 10 Nicole Brian 2 If someone asked us to summarize the information, we could simply state that the students earned 10, 0, and 2 thousand dollars, respectively. Now imagine data given for an entire class of 80 or 90 students. Could we look at the list of all of their earnings and discover an overall pattern? If so, could we identify any clear exceptions to this pattern? How could we briefly summarize the data, using just a few words or numbers? How were the data produced and measured? My data came from a sample of students attending class. Could we use information about their earnings to draw conclusions about the earnings of the population of all Pitt students? How reliable would those conclusions be?...
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- Fall '06