MATH:108:02 Introduction to Statistics Spring, 2015 Syllabus Instructor: Kenneth Brakke Office: 308 Fisher Hall Office phone: 4466 Email: brakke@susqu.edu I will use email to communicate with the class outside of meeting times, e.g. for homework corrections, hints, etc. So check your email regularly. When emailing me, be sure to use a good subject line. Blank subjects, and generic subjects like "question" and "help" are liable to get eaten by our spam filter. Use a subject like "Intro Stat homework question". Office hours: 1:00 - 3:00 MWF, 9:00 - 11:00 TTh officially. I am usually in my office 8:30 to 5:00 except for lunch and my classes 8:45-9:50 MWF, 10:00-11:05 MWF and 3:00-4:05 MWF. You can also make an appointment. Text: Introductory Statistics by Neil A. Weiss, 9th edition. Purpose: To learn basic statistics. The three main parts of statistics are 1. Descriptive statistics - summarizing and organizing data; histograms, averages, variance, percentiles, etc. 2. Probability - predicting the properties of a random sample from a known population. Probability rules, expected values, standard deviation, conditional probability, Bayes' Theorem. 3. Statistical inference - inferring the properties of a population from data about a randomly chosen sample. Sampling, significance, confidence intervals, hypothesis testing, p-values, linear regression. Grading: 3 Hour exams 50% Final exam 25% Daily homework, quizzes 25% Your final letter grade will be based on your course average, with the A-B-C-D cutoffs around the traditional 90-80-70-60 marks, but I may adjust that as I see fit. Homework: There will be daily homework assignments, to be handed in at the start of class. Each assignment will be graded. Assignments will include exercises using the computer statistics program Minitab or the spreadsheet program Excel. There will also be short in-class quizzes about every other class. At the end of the semester, there will be a small project, in which you design, carry out, and analyze a statistical experiment. Homework is due daily at the start of class, and will be graded. Late homework will get half credit, unless previous arrangements have been made (i.e. tell me when you are going to miss class for some excellent reason, or email me when you are too sick to come to class). Final exam: there will be a comprehensive final exam held in the official final exam period for this course, 11:30-1:30 Saturday, May 2. Tell your family not to plan family vacations, weddings, rides home etc. until after finals. OVER General: Roll will not be taken, but frequent absences will be noticed. You are still subject to the attendence policy in the Student Handbook. Policy on cheating: Don't. Studying together to understand the material is fine, but the work you hand in is to be your own. See the Student Handbook statement on academic honesty. My tests include writing definitions of vocabulary terms. Using the first sentence from a Wikipedia article as a definition is NOT a good idea: a. The article may be talking about a different meaning of the term. b. The article may use terms you don't know, like "exponentially bounded". c. The first sentence may be woefully incomplete as a definition. The lists of possible terms will be given on review sheets before the tests, and you should practice writing definitions of the terms, and THINK about what those definitions mean. This course satisfies the Central Curriculum Analytical Thought requirement. Central Curriculum Analytical Thought learning goals: 1. Abstract a problem into a symbolic or mathematical model or framework. Typically, problems in probability and statistical inference will be posed as word problems, and students will translate them into mathematical models. 2. Interpret such a model or framework in terms of a real- world construct. For a word problem, after solving the relevant mathematical problem, the mathematical result must be translated back into the terms of the original problem, in a form intelligible to an appropriate audience. 3. Reason from precisely stated principles using deductive methods and draw valid conclusions. Each type of mathematical model or problem-solving technique has specific prerequisites for its validity, and specific techniques for valid solution. 4. Recognize, manipulate and reason from or about abstract patterns. The abstract patterns involved here are centered around probability, randomness, sampling, error, and statistical inference.