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Math 3261/001 - Fall 2014 Statistical Methods Instructor: Dr. Nicolae R. Pascu Office: R2 329, Phone: (678) 915-4989 E-mail: [email protected] TEXTBOOK: Probability and Statistics, 8e, J. Devore (Brooks/Cole, Cengage learning). To enroll in class (WebAssign) use the key spsu 7210 3202. MEETING TIMES/LOCATION: MWF 11:00 am - 11:50 am/ J215B COURSE DESCRIPTIONThis course is designed to introduce the student to inferential statistics. Topics include: Central Limit Theorem, sampling distributions, statistical tests/confidence intervals for means and proportions, inferences for correlation and regression, multiple regression, Chi Square: tests of independence and goodness of fit test, testing and estimating a single variance or standard deviation (ANOVA). Appropriate technology may at times be used to complement the learning process. GOALS: Upon completing this course students should be able to: Understand Central Limit Theorem and its application to confidence intervals of mean and proportion; conduct hypothesis testing for mean, deviation, and proportion. Understand correlation and regression; know how to perform linear regression analysis. Test hypotheses involving one or two variances by using Chi-square and F distributions; perform one-way and two-way analysis of variance. OFFICE HOURS: MTuTh 8:10 – 9:00, W 9-10:50, or by appointment. PREREQUISITE: Prerequisite: MATH 2253. HOMEWORK: For each section, there will be a minimum number of problems, which I strongly suggest to be done by the next class meeting. Selected homework problems will be collected and graded. COURSE POLICY: Occasionally we will have a quiz or a group project. There will two inclass exams, tentatively scheduled for Sep 8th, and Oct 17th respectively. The final exam is cumulative (the date will be announced). There will be no make-up midterm exams. Evaluation: Input into semester grades will be as follows: - 25% Exam 1, - 25% Exam 2 - 20% HW/Projects - 30% Final Exam The scale for converting your score to letter grades is the usual one (90% or more is an A, 80-89% is a B, 70-79% is a C, 60 - 69% is a D, below 60% is a F). IMPORTANT DATES: Labor Day Holiday September 1st/ The last day to withdraw from class with a grade of "W" is October 2nd/ Thanksgiving Holiday November 26th – 28th/ Last day of classes Monday, December 1st. STUDENTS WITH DISABILITIES: Students with disabilities who believe that they may need accommodations in this class are encouraged to contact the counselor working with disabilities at (678) 915-7361from the ATTIC office (http://www.spsu.edu/ATTIC/) as soon as possible to better ensure that such accommodations are implemented in a timely fashion. NOTE: The pace may vary, so the following is a weekly rather than daily outline. MATH 3261/001 Statistical Methods COURSE OUTLINE WEEK Aug 13th -Aug 15th Aug 18th -Aug 22nd Aug 25th -Aug 29th Sep 1st -Sep 5th SECTIONS/TOPICS 3.1 Random variables 3.2 Probability distributions for discrete r.v. 3.3 Expected values 4.1 Probability density functions 4.2 Cumulative distribution functions and expected values 5.1 Jointly distributed r.v. 5.2 Expected value, covariance and correlation 5.3 Joint Probability Distributions and Random Samples 5.4 Joint Probability Distributions and Random Samples 6.1 Point Estimation 6.2 Methods of point estimation Labor Day Holiday Monday, September 1st Sep 8th -Sep 12th Sep 15th -Sep 18th Sep 22nd -Sep 25th Sep 29th -Oct 3rd Oct 6th -Oct 10th EXAM 1 7.1 Confidence intervals 7.2 Confidence intervals for a population mean and proportion 7.3 Intervals based on a normal population distribution 7.4 Confidence intervals for the variance and standard deviation 8.1 Hypotheses and Tests Procedures 8.2 Tests about a population mean 8.3 Tests concerning a population proportion 8.4 P-values 9.1 z-tests and confidence intervals for a difference between two population means 9.2 Two sample t-test and confidence interval Oct 13th -Oct 17th Oct 20th - Oct 24th Oct 27th -Oct 31st Nov 3rd -Nov 7th Nov 10th – Nov 14th Nov 17th – Nov 21st Nov 24th – Dec 1st Thanksgiving Holiday Nov 26th – Nov 28th 9.3 Analysis of paired data 9.4 Inferences for differences between population proportions 9.5 Inferences concerning two population variances EXAM 2 12.1 The simple linear regression model 12.2 Estimating model parameters 12.3 Inferences about the slope parameter 12.4 Inferences and prediction of future y-values 12.5 Correlation 14.1 Goodness of fit (category probabilities specified) 14.2 Goodness of fit for composite hypotheses 14.3 Two way contingency tables 10.1 Single factor ANOVA 10.2 Multiple comparisons in ANOVA Review for Final Examination