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Mathematics, Statistics & Computer Science Department COURSE NO./TITLE: CREDIT: STAT-320/520 (354-530) STATISTICAL METHODS 3 COURSE DESCRIPTION: Methods of describing data: graphical methods, numerical summary measures, exploratory data analysis. Probability, probability distributions, expected value. Sampling distributions. Statistical inference: estimation and hypothesis testing for one-sample and two-sample problems. Regression analysis. Demonstrating with standard statistical software packages. Prerequisite: MATH-120 or equivalent. TEXTBOOK: Introduction to the Practice of Statistics, 5th Ed., by Moore (adopted 8/06) (Adopted 6/98: Introduction to the Practice of Statistics, 3rd Ed., by Moore) (Adopted 8/93: 2nd Ed.; adopted 8/03: 4th) COURSE OBJECTIVES: The course will enable students to: 1. Demonstrate understanding of the basic principles of probability and statistics. 2. Demonstrate understanding of the relationship between probability and statistics and the importance of each in modeling practical problems. 3. Use of descriptive statistical methods, both numerical and graphical, to organize and summarize data. 4. Apply the inferential statistical methods of estimation and hypothesis testing. 5. Interpret the output of a statistical computing package. 6. Write clear, complete, and logically correct presentations of the statistical analyses performed in homework exercises and/or class projects. In addition, graduate students shall be able to: 1. Design, conduct, analyze and interpret their own statistical experiments in consultation with the instructor and present their results in written reports. 2. Demonstrate proficiency in the implementation of statistical procedures using a standard statistical computer package. COURSE OUTLINE: 1. Introduction 2. The Methods of Descriptive Statistics; Exploratory Data Analysis A. Frequency Distributions and Histograms B. Stem-and-Leaf Displays C. Box Plots D. Numerical Summary Methods E. Scatter Plots, Exploratory Regression Analysis, Correlation 3. Probability and Probability Distributions A. The Sample Space, Events and the Algebra of Events B. Definitions and Rules of Probability C. Conditional Probability; Independence; Bayes' Rule D. Random Variables and Probability Distributions 4. 5. 6. 7. Sampling Distributions A. Statistics and Random Samples B. Sampling Distribution of the Sample Mean C. Sampling Distribution of the Sample Proportion Statistical Inference for One and Two Sample Problems A. Concepts of Estimation; Confidence Intervals B. Concepts of Hypothesis Testing C. Large Sample Inference D. Small Sample Inference; the t Distribution Introduction to Simple Linear Regression Analysis A. The Method of Least Squares B. Inference in the Regression Model C. Estimation and Prediction Using the Regression Equation Analysis of Categorical Data (if time permits) Revised 6/08