INTRODUCTION TO PROBABILITY AND MATHEMATICAL STATISTICS II

Name: INTRODUCTION TO PROBABILITY AND MATHEMATICAL STATISTICS II
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MATH/STAT 310

과목 설명

Mathematical statistical inference aims at providing an understanding of likelihood's central role to statistical inference, using the language of mathematical statistics to analyze statistical procedures, and using the computer as a tool for understanding statistics. Specific topics include: samples and populations, estimation, hypothesis testing, and theoretical properties of statistical inference.

선수과목

(MATH/STAT 309 , STAT 311 , MATH/STAT 431 , or MATH 531 ) and (STAT 240 , STAT 301 , STAT 302, STAT 324 , STAT 371 , or ECON 310 ), or graduate/professional standing

충족 요건

FINANCE 325 , ISYE 649 , GENBUS 656 , SOC 351 , ISYE 445 , ACTSCI 652 , ISYE 615 , ISYE 562 , C&ESOC/SOC 361 , COMPSCI/STAT 471 , ISYE 320 , FINANCE 330 , BMI/STAT 641 , STAT 303 , ECON/FINANCE 320 , C&ESOC/SOC 365 , ISYE 575 , ISYE 620 , BMI/STAT 642 , SOC 674 , SOC 375 , C&ESOC/SOC 618 , ME 536 , ME/STAT 424 , ISYE 625 , and ACTSCI 640

학점

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평점

3.32

4.92% 과거 데이터 대비

수료율

97.18%

2.58% 과거 데이터 대비

A 비율

45.07%

25.56% 과거 데이터 대비

학급 규모

19.02% 과거 데이터 대비

Cumulative Grade Distribution

강사 (2026 Summr)

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유사 과목

STATISTICAL INFERENCE FOR DATA SCIENCE

STAT 612

Statistical models, methods and theory for parameter estimation, Bayesian approach to parameter estimation, methods and theory for hypothesis tests, confidence sets, two-sample testing and ANOVA, categorical data analysis, linear regression.

INTRODUCTION TO COMPUTATIONAL STATISTICS

COMPSCI/STAT 471

Classical statistical procedures arise where closed-form mathematical expressions are available for various inference summaries (e.g. linear regression; analysis of variance). A major emphasis of modern statistics is the development of inference principles in cases where both more complex data structures are involved and where more elaborate computations are required. Topics from numerical linear algebra, optimization, Monte Carlo (including Markov chain Monte Carlo), and graph theory are developed, especially as they relate to statistical inference (e.g., bootstrapping, permutation, Bayesian inference, EM algorithm, multivariate analysis).

MATHEMATICAL STATISTICS II

MATH/STAT 710

Estimation theory, efficiency, Neyman-Pearson theory of hypothesis testing, confidence regions, decision theory, likelihood ratio theory, current research topics in mathematical statistics.

INTRODUCTION TO THEORY AND METHODS OF MATHEMATICAL STATISTICS II

STAT 312

Unbiased estimation, maximum likelihood estimation, confidence intervals, tests of hypotheses, Neyman-Pearson lemma, likelihood ratio test, regression, analysis of variance with applications.

INTRODUCTION TO STATISTICAL INFERENCE

STAT 610

Conditioning, distribution theory, approximation to distributions, modes of convergence, limit theorems, statistical models, parameter estimation, comparision of estimators, confidence sets, theory of hypothesis tests, introduction to Bayesian inference and nonparametric estimation.