In the following course list, the Level II Statistics prerequisite may be fulfilled with 01:960:212 or 384 or 401 or 484 or equivalent. Credit is not given for more than one course fulfilling the Level II Statistics prerequisite.
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01:960:142
Data 101 (3)
Topics in data literacy for students not majoring in computer science or statistics.
Prerequisite: 01:640:025 or placement. Credit not given for both this course and 01:198:142.
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01:960:211,212
Statistics I,II (3,3)
Principles and methods of statistics, including frequency distributions, measures of central tendency and dispersion, simple probability, sampling, regression and correlation analysis, curve fitting, chi-square analysis, test of significance.
Prerequisite: 01:640:115 or permission of department. See Level II Statistics restrictions. Credit not given for more than one of 01:960:201, 211, and 285, nor for more than one of 01:960:212, 384, and 401.
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01:960:285
Introductory Statistics for Business (3)
Topics include descriptive statistics, probability, random variables, sampling distributions, principles of hypothesis testing, and one- and two-sample T-tests.
Prerequisite: 01:640:115 or equivalent. Credit not given for more than one of 01:960:201, 211, and 285.
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01:960:379
Basic Probability and Statistics (3)
Methods of presenting data; basic statistical measures of location; frequency distributions; elementary probability theory; probability distributions; the binomial, Poisson, and normal distributions; basic sampling theory.
Prerequisite: One semester of calculus.
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01:960:381
Theory of Probability (3)
Probability distributions; the binomial, geometric, exponential, Poisson, and normal distributions; moment-generating functions; sampling distributions; applications of probability theory.
Prerequisites: Three semesters of calculus.
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01:960:382
Theory of Statistics (3)
Statistical inference methods, point and interval estimation, maximum likelihood estimators, information inequality, hypothesis testing, Neyman-Pearson lemma, linear models.
Prerequisite: 01:960:381 or equivalent.
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01:960:384
Intermediate Statistical Analysis (3)
Application of statistical techniques to the analysis of data, tests of significance, correlation and regression analysis, confidence intervals, analysis of variance, and some design of experiments; analysis of cross-classified data, chi-square tests. Course requires the use of basic statistics computer package.
Prerequisite: One of the following courses: 01:960:201, 211, 285, 379, 381, or permission of instructor. Credit not given for both this course and 01:960:212 or 484 or 401. (Formerly 01:960:380.)
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01:960:390
Introductory Computing for Statistics (1)
Introduction to the use of statistics computer packages with main focus on the SAS system. Includes generating random samples, estimation, testing hypothesis, ANOVA.
Five-week course; 3 hrs. lec. and lab. Prerequisite: Level II Statistics. Graded on a Pass/Fail (undergraduate) and S/U (graduate) basis.
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01:960:391,392
Honors Seminars in Probability/Statistics (3,3)
Real-life examples or case studies on statistics and probability theory and their ramifications. Topics may vary each semester. Extensive data analysis required.
Prerequisite: CALC1 or permission of department. Corequisite: CALC2. Open to students in school honors programs.
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01:960:401
Basic Statistics for Research (3)
As applied in fields other than statistics; treats research projects dependent on the use of observed data from planned experiments. Includes inference methods in estimation and hypothesis testing and general linear models.
Prerequisite: 01:640:115 or equivalent. Credit not given for more than one of 01:960:212, 384, and 401.
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01:960:463
Regression Methods (3)
Multiple and nonlinear correlation and regression techniques for analysis of events in time and space: analysis of variance and covariance, related multivariate techniques, response surface approaches.
Prerequisite: Level II Statistics.
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01:960:467
Applied Multivariate Analysis (3)
Introduction to the methodology of multivariate analysis. Multiple linear regression, discriminant analysis, profile analysis, canonical correlation, principal components, and factor analysis.
Prerequisite: Level II Statistics or permission of department.
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01:960:476
Introduction to Sampling (3)
Principles of sampling application for economic procurement or assessment of data. Current techniques for area sampling, sampling of accounts, large-scale surveys, stratification, cluster sampling, systematic sampling, two-stage sampling, and construction of estimates.
Prerequisites: Level II Statistics and 01:960:379 or 381 or equivalent with a grade of C or better, or permission of department.
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01:960:483
Statistical Quality Control (3)
Statistical measures; histogram analysis; construction and analysis of control charts for variables and attributes; use of Dodge-Romig and Military Standards acceptance sampling plans; statistical aspects of tolerances.
Prerequisite: One semester of statistics at the college level.
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01:960:484
Basic Applied Statistics (3)
Confidence estimation, hypothesis testing, chi-square methods, correlation and regression analysis, basis of design of experiments.
Prerequisite: One of the following courses: 01:960:201, 211, 285, 379, 381, or permission of instructor. Credit not given for both this course and 01:960:212 or 384 or 401.
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01:960:486
Computing and Graphics in Applied Statistics (3)
Use of various computer-based techniques, including graphical, to understand and interpret data. Exposure to basic analysis of categorical, time-series, and multivariate data in applied areas such as biostatistics, quality control, and others.
Prerequisite: Level II Statistics.
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01:960:490
Introduction to Experimental Design (3)
Basic concept and principles of designs. Nature and analysis of various designs; randomized blocks, Latin squares, factorial designs. Applications to specific problems.
Prerequisite: Level II Statistics.
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01:960:491
Reliability-Quality Control (3)
Survey of current theory and practice in this field.
Prerequisites: 01:640:251 and Level II Statistics.
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01:960:495
Independent Studies in Statistics (3)
Prerequisite: Permission of department.
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