Rutgers, The State University of New Jersey
Undergraduate-New Brunswick
 
About the University
Undergraduate Education in New Brunswick
Programs of Study and Courses for Liberal Arts and Sciences Students
Programs, Faculty, and Courses
Availability of Majors
Course Notation Information
Accounting 010
African Area Studies 016
African, Middle Eastern, and South Asian Languages and Literatures 013
Africana Studies 014
Agriculture and Food Systems 020
American History 512
American Literature
American Studies 050
Animal Science 067
Anthropology 070
Archaeology 075
Architectural Studies 076
Armenian 078
Art 080
Art History 082
Arts and Sciences 090
Asian Studies 098
Astrobiology 101
Astrophysics 105
Biochemistry
Biological Sciences
Biomathematics
Biomedical Sciences
Biotechnology 126
Business Analytics and Information Technolgy 136
Business Law 140
Cell Biology
Chemistry 160
Chinese 165
Cinema Studies 175
Classics
Cognitive Science 185
Communication 192
Community Development
Comparative Literature 195
Computer Science 198
Criminal Justice 202
Criminology 204
Dance 203
Dentistry
Ecology, Evolution, and Natural Resources 216
Economics 220
Education 300
Engineering
English
Entomology 370
Environmental and Business Economics 373
Environmental Certificates
Environmental Planning 573
Environmental Policy, Institutions, and Behavior 374
Environmental Sciences 375
Environmental Studies 381
European Studies 360
Exercise Science 377
Film Studies
Finance 390
Food Science 400
French 420
Gender and Media 438
Genetics
Geography 450
Geological Sciences 460
German 470
Greek 490
Greek, Modern Greek Studies 489
Health Administration 501
Health and Society 502
Hindi
History
History/French Joint Major 513
History/Political Science Joint Major 514
Holocaust Studies 564
Human Resource Management 533
Hungarian 535
Individualized Major 555
Information Technology and Informatics 547
Interdisciplinary Studies, SAS 556
International and Global Studies 558
Italian 560
Japanese 565
Jewish Studies 563
Journalism and Media Studies 567
Junior Year Abroad
Korean 574
Labor Studies and Employment Relations 575
Landscape Architecture 550
Latin 580
Latin American Studies 590
Latino and Caribbean Studies 595
Law
Leadership and Management 605
Life Sciences
Linguistics 615
Management and Global Business 620
Marine Sciences 628
Marketing 630
Mathematics 640
Medicine and Dentistry
Medieval Studies 667
Meteorology 670
Microbiology 680
Middle Eastern Studies 685
Military Education, Air Force 690
Military Education, Army 691
Military Education, Naval 692
Military Science Minor (Military Science 691N, Naval Science 692N, Aerospace Science 693N, Non-Commissioning 695N)
Molecular Biology
Music
Nursing
Nutritional Sciences 709
Operations Research 711
Organizational Leadership 713
Pharmacy
Philosophy 730
Physics 750
Physiology and Neurobiology
Planning and Public Policy 762
Plant Biology 776
Polish 787
Political Science 790
Portuguese 810
Psychology 830
Public Health 832
Public Policy 833
Religion 840
Russian 860
Sexualities Studies 888
Social Justice 904
Social Work 910
Sociology 920
South Asian Studies 925
Spanish 940
Sport Management 955
Statistics 960
Learning Goals
Major Requirements
Sequence of Courses for Nonmajors
Minor Requirements
Courses
Statistics-Mathematics
Study Abroad 959
Supply Chain Management 799
Theater 965
Ukrainian 967
Urban Planning and Design 971
Urban Studies
Visual Arts
Women's, Gender, and Sexuality Studies 988
World Language Proficiency Certificates
School of Arts and Sciences
School of Environmental and Biological Sciences
Mason Gross School of the Arts
Ernest Mario School of Pharmacy
Rutgers Business School: Undergraduate-New Brunswick
School of Communication and Information
School of Engineering
Edward J. Bloustein School of Planning and Public Policy
School of Management and Labor Relations
Honors College of Rutgers University-New Brunswick
General Information
Divisions of the University
Camden Newark New Brunswick/Piscataway
Catalogs
New Brunswick Undergraduate Catalog 2022-2024 Programs of Study and Courses for Liberal Arts and Sciences Students Programs, Faculty, and Courses Statistics 960 Courses  

Courses


In the following course list, the Level II Statistics prerequisite may be fulfilled with 01:960:212 or 291 or 384 or 401 or 484 or equivalent. Credit is not given for more than one course fulfilling the Level II Statistics prerequisite.

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.
01:960:211,212 Statistics I,II (3,3) Principles and methods of statistics, including probability distributions, sampling, estimation, hypothesis testing, regression and correlation analysis, chi-square analysis, analysis of variance, tests of significance. 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.
Prerequisite: 01:640:115 or permission of department. See Level II Statistics restrictions. Credit not given for both this course and either 01:960:384 or 484. Credit not given for both this course and 01:960:401 unless 401 is being used, with permission of the department, as a prerequisite for this course.
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, 285, or 401.
01:960:291 Statistical Inference for Data Science (3) Introduction to probability and statistics underlying data science. Topics include regression, resampling, confidence intervals, hypothesis testing, and related probability distributions. Prerequisites: 01:640:115 and (01:198:142 or 01:960:142).
01:960:295 Data Management and Wrangling with R (3) An introduction to the tools and principles to retrieve, tidy, clean, and visualize data in preparation for statistical analysis. The R statistical environment is used but no prior knowledge is required. Interactions with databases will be included. Prerequisite: 01:198:142 or 01:960:142 or 01:960:291 or 01:960:212 or 01:960:384 or 01:960:401.
01:960:365 Introduction to Bayesian Data Analysis (3) Principles of Bayesian data analysis and application of them to varied data analysis problems. Topics include: Bayes Theorem, linear and nonlinear models, hierarchical models, and the use of Markov chain Monte Carlo methods. Prerequisites: Level II Statistics and 01:640:152.
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.
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.
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.
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.
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. Credit not given for both this course and 01:960:401 unless 401 is being used, with permission of the department, as a prerequisite for this course.
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.
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: Calculus 1 or permission of department. Corequisite: Calculus 2. Open to students in school honors programs.
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 both this course and 01:960:211, 212, 384, and/or 484. Students who have already taken 01:960:401 and wish to take any of these courses should consult with the department.
01:960:435 Seminar in Probability and Statistical Inference (3) Examines statistical theory, including topics such as Bayesian inference, confidence intervals, and maximum likelihood, to prepare students to use, discuss, and criticize statistical methods in a way that is both mathematically sound and historically informed. Prerequisite: 01:960:382 or equivalent or permission of instructor.
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
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.
01:960:476 Introduction to Sampling (3) Principles of sampling applied for economical 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.
01:960:482 Advanced Issues in Probability and Statistics (3) Focus on understanding both the power and limitations of statistical techniques and principles as applied in real-world settings. Includes projects involving the collection of data to be analyzed and discussed. Prerequisites: 01:960:382 and permission of instructor.
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: Level II Statistics or 33:623:385.
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.
01:960:486 Applied Statistical Learning (3)
Introduction to machine learning methods from a statistical perspective. Both traditional methods such as logistic regression, naive Bayes classification, and discriminant analysis as well as more recent statistical methods such as regularization, boosting, and random forests will be applied to datasets of varying size. The emphasis will not be on programming the techniques from scratch but on understanding and applying the methods using a high level language such as R. Prerequisites: Level II Statistics.
Prerequisite: Level II Statistics.
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.
01:960:491 Reliability-Quality Control (3) Survey of current theory and practice in this field. Prerequisites: 01:640:251 and Level II Statistics.
01:960:492 Special Topics in Statistics and Probability (3) Readings and presentations related to the development of probability and statistics. Prerequisite: Permission of instructor.    
01:960:495 Independent Studies in Statistics (3) Prerequisite: Permission of department.
 
For additional information, contact RU-info at 732/932-info (4636) or colonelhenry.rutgers.edu.
Comments and corrections to: Campus Information Services.

© 2022 Rutgers, The State University of New Jersey. All rights reserved.