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Introduction to Statistics Mathematics 146 spring 2014 12:00–1:05 p.m. M T W Th in room CC 3455 instructor: Ralph Jenne, phone & voice mail: (206) 934-4512 office: IB 2423 A office hours: 11–12 W, 1:30 – 2:30 M T Th, 5:30–5:55 T Th email: [email protected] website URL: http://facweb.northseattle.edu/rjenne Welcome to Statistics Statistics is a mathematical science devoted to data – how it can be intelligently collected, organized, analyzed, and interpreted. This introductory course has three main parts: (1) descriptive statistics, which introduces graphical presentations of data and measures of data sets, such as the mean and the standard deviation, (2) probability theory, which tries to quantify how likely events are to occur, and (3) inferential statistics, in which data collected from subgroups is analyzed to reach conclusions about the entire larger group. In order to make learning the subject easier for yourself and all the students in the class, please • ask questions when something is not clear • attend the class regularly • work the homework problems thoroughly. It’s not possible to become proficient in mathematics without doing it yourself. Give yourself an hour or two for each hour in class to work through each day’s assignment • browse through the material for each day before class. We’ll usually discuss a section or so of the book each day • take advantage of the Math Learning Center (CC 1353 A) for tutoring help. it’s open every day (except Saturday). or visit me during my office hours. • be respectful of others in the class. • refrain from talking with neighbors unless we’re working problems in class In my commitment to student learning I want to support all students. If you have a disability that will affect your performance in this class please let me know. Students with disabilities are encouraged to use Disability Services for support in implementing reasonable accommodations for their disabilities. I’ll spend most of the class time explaining the concepts and presenting examples showing how the concepts are applied. I welcome questions at any time. There will be portions of class time where you get a chance to solve some problems. Keeping up with the new concepts through homework exercises is essential to success in the course, and I will periodically ask you to hand in your assignments. There will be three tests during the quarter and a comprehensive final exam. There will be an opportunity to make-up one of the three tests by the way I score the final exam. I look at each section of the comprehensive final (a test one part, a test two part , and a test three part) and look to see on which section you have improved the most. If you have, for example, improved the most on the test two part of the final exam, then the score on the test two portion of the final replaces your original test two score. Of course, if the final exam scores are all lower, your original test scores are left unchanged. what you’ll need book: “Elementary Statistics, Picturing the World”, 5th edition, by Ron Larson & Betsy Farber, Pearson Prentice Hall, 2012 prerequisite: completion of intermediate algebra (Mathematics 098) with a grade of 2.5 or above calculator: You will need a scientific calculator. Graphing calculators are not required but may be helpful. Graphing calculators can be rented for a nominal fee from the math/science office. please turn off the sound on all cellphones and refrain from texting during class grades Each of the three tests and the final exam will count as 100 points, and homework, quizzes, and projects will count as a smaller number of points. Your percentage corresponds to decimal grades according to the scale 93% and up 3.9 or 4.0* 90% 3.8 80% 3.0 70% 2.0 60% 1.0 50% 0.7 under 50% 0.0 or NC * A course percentage of at least 93%, and a score of at least 90% on each test earns a 4.0. Other grades are linearly interpolated. For example, a score of 85% corresponds to a grade of 3.4. course outline • descriptive statistics (Chapters 1 & 2) (weeks one and two) – introduction (1.1) # 1–7 odd, 13, 15, 19, 23, 25, 29, 31, 35, 37, 41 – data classification (1.2) # 5, 7, 11, 13, 19, 25, 27, 29 – experimental design (1.3) # 1, 5, 9, 11, 13, 15, 19–25 odd, 31, 35, 43 – frequency distributions & their graphs (2.1) # 3, 7, 11, 15, 17, 19, 21, 23, 25, 27 – more graphs (pie charts, scatter plots, and more) (2.2) # 1, 4, 5–15 odd, 23, 25, 29, 39 – measures of central tendency: median, mean, mode (2.3) # 1, 5, 7, 9, 13, 15, 19, 27, 31, 33, 37, 39, 41, 47, 49 – measures of data spread: standard deviation (2.4) # 1, 5, 9, 11, 13, 15, 17, 21, 25, 29, 31, 33, 37, 39, 41, 47 – measures of position: quartiles, percentiles (2.5) # 1, 3, 7, 13, 17, 19, 21, 27, 29, 35, 37, 41, 43, 45, 47 • probability and probability distributions (Chapters 3,4,5) (weeks 3,4,5) – probability and counting (3.1) # 1, 2, 5, 9, 11, 17, 19, 21, 25, 29, 31, 35, 39, 43, 45, 47, 49, 53, 57, 61, 69, 73 – conditional probability and independence of events (3.2) # 1–17 odd, 23, 25, 27, 31, 41 – mutually exclusive events (3.3) # 1–11 odd, 15, 17b, 19c, 23 a, d – permutations & combinations (3.4) # 3, 7, 11, 15, 17, 19, 23, 25, 35, 39, 41, 49, 51, 55b – probability distributions, random variables (4.1) # 1, 5–27 odd, 31, 37, 41, 45 – binomial distributions (4.2) # 1, 3, 9, 13, 17, 25, 31, 33 – normal distributions (5.1) # 3, 5, 11–25 odd, 29, 33, 37, 43, 45, 53, 57, 59 – calculating probabilities with normal distributions (5.2) # 1, 5, 9, 11, 13, 21, 23, 29 – determining values with normal distributions (5.3) # 3, 7, 11, 15, 17, 19, 25, 27, 31, 33, 37 – sample distributions & the central limit theorem (5.4) # 3, 5, 9, 15, 17, 23, 29, 31, 33 – normal approximations to the binomial distribution (5.5) # 13, 15, 23, 27, 31 • inferential statistics (rest of quarter) – confidence intervals for the mean (6.1) # 1, 3, 9, 11, 13, 19, 21, 23, 27, 31, 35, 43, 59 – confidence intervals for population proportions (6.3) # 1, 5, 7, 11, 13, 17, 21a, 23a – introduction to hypothesis testing (7.1) # 1–21 odd, 25, 29, 31, 33, 37, 39, 43, 45, 51, 57, 59 – hypothesis testing for the mean (7.2) # 3, 5, 7, 9, 13–29 odd, 37 – hypothesis testing for a proportion (7.4) # 3, 11, 15, 17 – testing the difference between means (8.1) # 1, 5, 7, 13, 15, 21, 23, 27 – correlation (9.1) # 1–19 odd, 31 – linear regression (9.2) # 1–17 odd – other topics (as time allows) • no class: Memorial Day, May 26 (and probably May 9) • last class meeting before final exam: Tuesday, June 17 • final exam: Thursday, June 19, 1–3 p.m.