Search

• MATH 364: Mathematical Statistics II

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  Multivariate distributions, change of variable technique, chi-square distribution, estimation, confidence intervals, hypothesis testing, contingency tables, goodness of fit. Practical applications are used to aid in the development. Prerequisite:    MATH 363
  ShareMATH 364 - Mathematical Statistics II

• MATH 371: Linear Algebra

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  Vector spaces and linear transformations are studied in a theoretical setting. Also, canonical forms and multilinear algebra are studied. Prerequisite:    MATH 171, 271 with a C or better grade
  ShareMATH 371 - Linear Algebra

• MATH 411: Univariate Data Analysis

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  An applied statistics course in descriptive statistics, statistical inference procedures, regression analysis, analysis of variance, and analysis of deviance. Inference procedures for population means and proportions are developed. Simple linear regression, multiple linear regression, one way ANOVA, two way ANOVA, Poisson regression, and logistic regression models are used to analyze data. Emphasizes the applied aspects of these statistical models and uses computer software for data analysis. Prerequisite:    MATH 214, 216, or 217 or permission of the instructor
  ShareMATH 411 - Univariate Data Analysis

• MATH 412: Multivariate Statistics

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  An applied statistics course that focus on multivariate statistical methods. Research procedures on the relationship among variables, significance of group differences, prediction of group membership, and structure exploration are introduced. Factorial analysis of variance, analysis of covariances, multivariate analysis of variance and covariance, path analysis, factor analysis and discriminate analysis are introduced and used to analyze data. Emphasizes the applied aspects of these statistical methods and uses computer software for data analysis. Prerequisite:    MATH 214, 216 or 217, or permission of the instructor
  ShareMATH 412 - Multivariate Statistics

• MATH 413: Methods for Teaching Mathematics

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  Examines the current curricula and methods of instruction used in middle and secondary level mathematics classrooms. Follows an investigative approach to middle-level and secondary mathematics instruction through hands-on activities that are standards based. Explores methods of teaching in diverse classrooms and teaching students with special needs.
  ShareMATH 413 - Methods for Teaching Mathematics

• MATH 416: Time Series Analysis

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  Applied statistics course in the analysis and forecasting of time series data. Linear time seriesregression models, ARIMA models, SARIMA models, GARCH models, and spectral theory are usedto examine time series data. Emphasizes the applied aspects of these models. Computer software is used for data analysis. Prerequisite:    MATH 363 or MATH 411 or ECON 356 or permission of the instructor
  ShareMATH 416 - Time Series Analysis

• MATH 418: Data Science Theory and Application

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  Covers acquiring, managing, and analyzing massive unstructured data through a project-driven approach. Includes theoretical analysis of clustering, visualization, link analysis, recommendation systems, mining social network graphs, dimensionality reduction with PCA and SVD, large-scale machine learning, neural nets and deep learning, distributed file systems, incremental data processing with Hadoop, NoSQL databases, cloud computing, and data security issues. Covers applications in web advertising, business, engineering, health care and social networks. Implements a computational project utilizing machine learning and artificial intelligence techniques.
  ShareMATH 418 - Data Science Theory and Application

• MATH 420: Patterns and Functions for Elementary / Middle-Level Teachers

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  Examines and develops expertise with sequences, patterns, and functions, including linear, quadratic, logarithmic, exponential, and trigonometric functions. Appropriate technology is incorporated throughout the course. Explores curricular materials, resources, and activities relevant to teaching diverse groups at the Elementary/Middle Level. Prerequisite:    MATH 152
  ShareMATH 420 - Patterns and Functions for Elementary / Middle-Level Teachers

• MATH 421: Advanced Calculus I

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  Study of set theory, real number system, functions topology of Cartesian space, sequences, convergence and uniform convergence, continuity, and uniform continuity. Prerequisite:    MATH 272 with a grade of C or better
  ShareMATH 421 - Advanced Calculus I

• MATH 422: Advanced Calculus II

  3.00 Credits

  Indiana University of Pennsylvania-Main Campus

  
  Includes the study of convergence sequences in Rn, global properties of continuity, uniform continuity, differentiation of Rn, Riemann integrals, and infinite series. Prerequisite:    MATH 421
  ShareMATH 422 - Advanced Calculus II