Rutgers, The State University of New Jersey
Camden Undergraduate
About the University
Undergraduate Education in Camden
Degree Requirements
Liberal Arts Colleges
Camden College of Arts and Sciences
University College-Camden
Programs, Faculty, and Courses
Course Notation Information
Availability of Majors
Accounting 010
Africana Studies 014
American History 512
American Literature 352
Anthropology 070
Art 080
Art History 082
Arts and Sciences 090 (Interdisciplinary Courses)
Astronomy 100
Biochemistry 115
Biology 120
Biology, Computational and Integrative 121
Business Administration 135
Business Law 140
Chemistry (Biochemistry 115, Chemistry 160)
Childhood Studies 163
Computer Science 198
Criminal Justice 202
Dance 203
Digital Studies 209
Economics 220
Engineering Transfer 005
English and Communication (Communication 192, English Literature 350, American Literature 352, Film 354, Journalism 570, Linguistics 615, Rhetoric 842, Writing 989)
Finance 390
Forensic Science 412
French 420
Gender Studies 443
Geology 460
German 470
Global Studies 480
Health Sciences 499
History (Historical Methods and Research 509; European History 510; American History 512; African, Asian, Latin American, and Comparative History 516)
Honors College 525
Human Resource Management 533
Individualized Majors and Minors 555
Journalism 570
Latin American and Latino Studies (LALS) Minor
Learning Abroad
Liberal Studies 606
Linguistics 615
Management 620
Management Science and Information Systems 623
Marketing 630
Mathematical Sciences (Mathematics 640, Statistics 960)
Major Requirements
Bachelor of Science in Mathematics
Bachelor of Science in Applied and Computational Mathematics
Bachelor of Science in Mathematics and Statistics for Artificial Intelligence and Data Science
Bachelor of Science in Mathematical Biology
Bachelor of Arts in Mathematics -Teaching
Minor Requirements
Accelerated Bachelor and Master Degree Programs
Departmental Honors Program
Courses (Mathematics 640)
Courses (Statistics 960)
Medicine, Dentistry, and Veterinary Medicine
Museum Studies 698
Music 700, 701
Pharmacy 720
Philosophy and Religion 730, 840
Physics 750
Political Science 790
Psychology 830
Religion 840
Reserve Officer Training Programs
Social Work 910
Sociology (920), Anthropology (070), and Criminal Justice (202)
Spanish 940
Statistics 960
Teacher Education 964
Theater Arts (Dance 203, Theater Arts 965)
World Languages and Cultures (French 420, German 470, Global Studies 480, Spanish 940)
Urban Studies 975
Visual, Media, and Performing Arts (Art 080; Art History 082; Museum Studies 698; Music 700, 701; Theater Arts 965)
Rutgers School of Business-Camden
School of Nursing-Camden
Academic Policies and Procedures
Divisions of the University
Camden Newark New Brunswick/Piscataway
  Camden Undergraduate Catalog 2021-2023 Liberal Arts Colleges Programs, Faculty, and Courses Mathematical Sciences (Mathematics 640, Statistics 960) Courses (Statistics 960)  

Courses (Statistics 960)

50:960:183 Elementary Applied Statistics (R) (3) Frequency distribution, graphical representations, measures of central tendency and variability, elements of probability, the normal curve and its applications, sample versus population, estimating and testing hypotheses, regression and correlation analysis, nonparametric tests. Emphasis on applications. No prerequisite beyond the usual three years of high school mathematics. Credit will not be given for both this course and 50:830:215.
50:960:185 Introduction to Data Science (3) Data structures, data wrangling, data mining, inferential thinking, and statistical computations. No prerequisite beyond the usual three years of high school mathematics.
50:960:283 Introduction to Statistics I (R) (3) Introductory course in the theory and methods of statistics. Topics include measures of central tendency and dispersion, probability theory, random variables and probability distribution, binomial and normal distributions, central limit theorem, confidence intervals, and testing of hypotheses on mean(s) and proportion(s). Prerequisite: 50:640:113 or 115. Intended primarily for business majors and information systems/computer science majors.
50:960:284 Introduction to Statistics II (R) (3) A second introductory statistics course. Emphasizes the application of statistical techniques to data analysis. Topics include analysis of variance, nonparametric statistics, simple linear regression, correlation, multiple regression, time series, and index numbers. Prerequisite: 50:960:283. Intended primarily for business majors and information systems/computer science majors.
50:960:336 Applied Statistics (3) Descriptive statistics, probability, random variables, probability distributions, computer simulations, estimation and tests of hypotheses, and regression and correlation analysis. Emphasis on applications of these techniques to problems in the biological, physical, and social sciences. Prerequisite: 50:640:122. Intended primarily for applied mathematics majors but open to all qualified students.
50:960:340 Special Topics in Statistics (3) Aimed at students with any major who want to go beyond the first two statistics courses. Instructor provides proper description. Prerequisite: 50:960:284.
50:960:384 Statistical Data Analysis (3) Aimed at students who want to go beyond the first two statistics courses. Application of statistical techniques to analyze data. Topics include correlation and regression analysis, regression diagnostics, model building, design of experiments, and categorical data analysis. Use of computer packages for visual analysis and interpretation of data. Prerequisite: 50:960:284.
50:960:390 Introductory Computing for Statistics (3) Aimed at students who want to learn statistical computing along with or after the second statistics course. Introduces statistical computing using packages (Excel, SAS, etc.). Includes computing basic univariate statistics, generating random numbers, computing point estimates and confidence interval, testing of hypothesis, basic ANOVA, and regression. Pre- and corequisites: 50:960:283, 284.
50:960:452 Introduction to Biostatistics (3) Introduction to the principles and methods of statistical inference for advanced undergraduate and graduate students in the biological sciences. Topics include discussion of random variables, probability distributions, population, sample, measures of central tendency and dispersion, point and interval estimation, testing hypothesis, two-sample comparison, analysis of variance, linear regression and correlation model, and nonparametric methods. Emphasizes applications of statistical principles and analyses for biological sciences. Prerequisite: 50:640:121 or 130.
50:960:467 Introduction to Applied Multivariate Analysis (3) Aimed at students with any major who want to go beyond the first two statistics courses. Introduction to applied multivariate analysis through multivariate normal distribution. Topics include comparison of mean vector, multiple linear regression, discriminant analysis, principal components, factor analysis, and other applied multivariate topics. Use of statistical packages to perform the multivariate computation and its interpretation. Prerequisite: 50:960:284.
50:960:476 Introduction to Sampling (3) Application of the principles of sampling to economic procurement or assessment of data. Introduction to various sampling procedures. Emphasis on the design and control phases of investigation. Applications of the techniques to large-scale surveys, accounting and auditing, and operations research. Prerequisite: 50:960:283 or 336 or permission of instructor.
50:960:481,482 Mathematical Theory of Statistics (3,3) First semester: theory of probability, discrete and continuous probability distributions, introduction to statistical inference. Second semester: further study of distribution functions, correlation and regression, analysis of variance and design of experiments, nonparametric methods, sequential sampling. Prerequisite: 50:640:122 or permission of instructor.
50:960:483 Statistical Quality Control (3) Basic course in modern statistical quality control. Examines statistical measures, histogram analysis, construction and analysis of control charts for variables and attributes, use of Dodge-Roming and military standards acceptance sampling plans, and statistical aspects of tolerances. Prerequisite: 50:960:283 or permission of instructor.
50:960:484 Statistical Computing by SAS (3) Aimed at students who want to learn statistical computing along with or after the second statistics course. Topics include introduction to SAS for reading data, creating data sets, and handling other data steps. Using SAS to perform basic regression and model-building techniques. Carrying out ANOVA procedures for different design of experiments. Exposure to basic analysis of categorical, time series, and other types of data. Pre- and corequisites: 50:960:283, 284.
50:960:485-486 Number Problems in Mathematical Theory of Statistics (2,2) Numerical problems applied to data in student's field of study where possible. Emphasis on application of mathematical statistical distributions and methods. To be used as laboratory in conjunction with 50:960:481,482.
50:960:487-488 Introduction to Operations Research (3,3) A two-semester introduction to techniques of operations research involved in construction and solution of models in inventory, linear programming, nonlinear programming, queuing, sequencing, network, replacement, reliability, Markov chains, and competitive problems. Prerequisites: 50:960:283, 284, or permission of instructor.
50:960:489 Statistical Models (3) Introduction to multiple linear regression and its diagnostics, estimation, and testing in regression.  Analysis of variance models (ANOVA), regularized regression: ridge and lasso, and generalized linear models. Prerequisite: 50:640:331.
50:960:490 Experimental Design and Analysis (3) An advanced course in statistics with applications in all fields of study. Analysis of variance and covariance, experimental framework and layout, simple randomized designs, randomized blocks. Latin squares, Graeco-Latin squares, factorials, balanced and partially balanced designs, gains in precision and estimation. Prerequisites: 50:960:283, 284, or permission of instructor.
50:960:491 Regression and Time Series (3) Introduction to time series models, stationary processes, measure of dependence, tests of randomness, forecasting, estimation, model selection, ARIMA and ARMA models, and bootstrapping and smoothing. Prerequisite: 50:960:489.
50:960:492 Actuarial Models (3) Distribution theory and its convolution, application to loss models, failure times and censored data models, survival models: parametric and nonparametric, estimation, and model building. Prerequisite: 50:960:489.
50:960:495 Independent Study in Statistics (3) Intended for students who want to concentrate on special methods of statistical analysis and their applications to real-world problems. Prerequisites: 50:960:283, 284, and permission of instructor.
50:960:496 Independent Study in Operations Research (3) Intended to meet the needs of students who wish to study special techniques of operations research beyond the level of 50:960:487-488, or their applications to real-world problems. Prerequisites: 50:960:487-488 and permission of instructor.
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