Statistics

145. Introduction to Statistics. (3)


**345. Elements of Mathematical Statistics and Probability Theory. (3)


425 / 525. SAS® Programming. (3)


427 / 527. Advanced Data Analysis I. (3)


428 / 528. Advanced Data Analysis II. (3)


434 / 534. Contingency Tables and Dependence Structures. (3)


440 / 540. Regression Analysis. (3)


445 / 545. Analysis of Variance and Experimental Design. (3)


453 / 553. Statistical Inference with Applications. (3)


461 / 561. Probability. (3)


470 / 570. Industrial Statistics. (3)


472 / 572. Sampling Theory and Practice. (3)


474 / 574. Biostatistical Methods: Survival Analysis and Logistic Regression. (3)


476 / 576. Multivariate Analysis. (3)


477 / 577. Introduction to Bayesian Modeling. (3)


479. Topics in Statistics. (3, no limit Δ)


481 / 581. Introduction to Time Series Analysis. (3)


495. Individual Study. (1-3 to a maximum of 6 Δ)


520. Topics in Interdisciplinary Biological and Biomedical Sciences. (3, unlimited Δ)


524. Collaborative Interdiciplinary Teaching. (3)


525 / 425. SAS® Programming. (3)


**527 / 427. Advanced Data Analysis I. (3)


528 / 428. Advanced Data Analysis II. (3)


531. Statistical Genetics I. (3)


532. Statistical Genetics II. (3)


534 / 434. Contingency Tables and Dependence Structures. (3)


538. Biostatistical Methods I for Public Health and Medical Sciences. (3)


539. Biostatistical Method II for Public Health and Medical Sciences. (3)


540 / 440. Regression Analysis. (3)


545 / 445. Analysis of Variance and Experimental Design. (3)


546. Theory of Linear Models. (3)


547. Multivariate Analysis and Advanced Linear Models. (3)


553 / 453. Statistical Inference with Applications. (3)


556. Advanced Statistical Inference I. (3)


557. Advanced Statistical Inference II. (3)


561 / 461. Probability. (3)


565. Stochastic Processes with Applications. (3)


567. Advanced Probability. (3)


569. Selected Topics in Probability Theory. (3, no limit Δ)


570 / 470. Industrial Statistics. (3)


572 / 472. Sampling Theory and Practice. (3)


574 / 474. Biostatistical Methods: Survival Analysis and Logistic Regression. (3)


576 / 476. Multivariate Analysis. (3)


577 / 477. Introduction to Bayesian Modeling. (3)


579. Selected Topics in Statistics. (3, no limit Δ)


581 / 481. Introduction to Time Series Analysis. (3)


585. Nonparametric and Robust Methods. (3)


586. Nonparametric and Robust Methods. (3)


590. Statistical Computing. (3)


595. Problems. (1-3, no limit Δ)


599. Master’s Thesis. (1-6, no limit Δ)


605. Graduate Colloquium. (1 to a maximum of 4 Δ)


649. Seminar in Probability and Statistics. (1-3, no limit Δ)


650. Reading and Research. (1-6 to a maximum of 12 Δ)


699. Dissertation. (3-12, no limit Δ)


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MSC 11 6325
1 University of New Mexico
Albuquerque, NM 87131

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