STATISTICS 324, Spring 2004INTRODUCTORY APPLIED STATISTICS FOR ENGINEERSINSTRUCTOR: Greg Reinsel Office: 4361 Comp. Sci.-Stat. Phone: 262-0087E-mail: [email protected]://www.stat.wisc.edu/∼reinselTEACHING ASSISTANT: Chunpeng Fan Office: 4287 Comp. Sci.-Stat Phone: 262-7173E-mail: [email protected]: J. Devore, Probability & Statistics for Engineers, 6th edn, Brooks/ColeLECTURES: 2:30 – 3:45 TR, Room 1221 Comp. Sci.-Stat.FINAL EXAM: 5:05, Tuesday, May 11COURSE REQUIREMENTS:The grade in the course will be determined by two midterm exams each counting 25% towardthe final grade, weekly homework assignments counting about 17%, and a final exam countingabout 33%. Course content based on lectures, handouts, and textbook.Assignments will consist mainly of problems taken from the textbook, and occasionaloccasional additional assigned exercises including the analysis of data sets.Minitab (also R and Splus) computer packages will be discussed and used in later parts of course,but student may use any familiar means for performing necessary calculations for assignments.Tentative Outline and Schedule of Topics1. Treatment of Data and Descriptive Statistics (1 week)Dot diagrams, histograms, stem-and-leaf displays; descriptive measures: sample mean, me-dian, variance, standard deviation; quantiles and percentiles; boxplots.Devore, Sections 1.1–1.42. Basic Probability Concepts (1-1/2 week)Sample space and events, probability axioms, elementary rules of probability, independentevents, conditional probability, Bayes’ Theorem.Devore, Sections 2.1–2.53. Random Variables and Probability Distributions (3-1/2 week)Random variables, discrete and continuous, probability distributions, distribution functionand probability density function; mean and variance of a probabilty distribution; specialdiscrete distributions: binomial, geometric, negative binomial, Poisson, multinomial; specialcontinuous distributions: normal, uniform, log-normal, gamma, Weibull; joint probabilitydistributions.Devore, Sections 3.1–3.6, 4.1–4.6, 5.1–5.2MIDTERM EXAM 14. Random Samples and Sampling Distributions (1 week)Populations and samples, sample statistics, sampling distribution of sample mean¯X, proper-ties of linear combinations of random variables, sampling distribution of sample variance S2,t-distribution, chi-square (χ2) distribution, F distribution.Devore, Sections 5.3–5.5-2-5. Inferences Concerning Means and Variances (2-1/2 weeks)Methods of statistical inference, point and confidence interval estimation of parameters, meth-ods of estimation, tests of hypotheses, inference procedures concerning one mean (one sample),inference procedures concerning two means (two samples); estimation of variances, inferenceprocedures concerning one variance (one sample) or two variances (two samples); checkingnormality of a sample, normal probability (normal scores) plot.Devore, Sections 6.1–6.2, 7.1–7.4, 8.1–8.2, 8.4, 9.1-9.3, 9.56. Inferences Concerning Proportions and Categorical Data (1-1/2 weeks)Estimation of proportions, hypotheses concerning one proportion (one sample), hypothesesconcerning two proportions (two samples), hypotheses concerning several proportions, analy-sis of two-way contingency tables, tests for independence, chi-square tests for goodness-of-fit.Devore, Sections 7.2, 8.3, 9.4, 14.1–14.37. Simple (and Multiple) Linear Regression and Least Squares (1 week)Method of least squares estimation, properties of least squares estimators, inferences basedon least squares estimators, checking adequacy of the model; correlation; regression usingtransformed variables; multiple linear regression.Devore, Sections 12.1–12.5, 13.1–13.4MIDTERM EXAM 28. Analysis of Variance with One Factor (1 week)Completely randomized design, one-way layout (one-way ANOVA) model, randomized blockdesign, multiple comparisons.Devore, Sections 10.1–10.39. Factorial Experimentation (1 week)Two-factor experiments, replication, main effects and interactions, multi-factor experiments,2-level (2k) factorial experiments, fractional replication, confounding.Devore, Sections 11.1–11.4FINAL