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)


582. Advanced 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)


597. Statistical Consulting Laboratory. (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
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