I completed the following courses during my graduate training at Penn State University: 

Human Development and Family Studies Core Content

  • HD FS 501 Human Development across the Life Span

  • HD FS 503 Human Development Intervention: Analysis of Theories and Approaches

  • HD FS 515 Professional Issues in Human Development and Family Studies

  • HD FS 525 Introduction to Family Studies

Prevention and Intervention Research Specialization

  • HD FS 506 Design and Evaluation of Prevention and Health Promotion Programs Across the Life Span

  • HD FS 508 Best Practices in Preventive Intervention

  • HD FS / NUTR 532 Childhood Obesity

Developmental Methodology Specialization

  • HD FS 516 Methods of Research in Human Development

    • Introduction to research design; Sampling strategies; Descriptive statistics (data distributions); Hypothesis testing (t-tests, correlation, regression, one-way ANOVA, two-way ANOVA).

  • HD FS 518 Applied Statistics Laboratory

    • Complement to HD FS 516. SAS and SPSS procedures for descriptive statistics, t-tests, effect size and power, correlation, simple linear regression, one-way ANOVA, planned/post-hoc comparisons, two-way ANOVA; Interactions

  • HD FS 519 Methods of Statistical Analysis in Human Development

    • Variance and covariance; Least squares slopes and inference; Regression ANOVA decomposition; Regression diagnostics; Logistic regression; Matrix representation regression model; Multiple predictors; Inference for experiments and observational studies; Diagnostics for multiple predictors; Interactions; Suppression

  • HD FS 523 Strategies for Data Analysis in Developmental Research

    • Patterns in correlation, covariance, and sums of squares and cross products matrices, ANOVA and ANCOVA designs (planned and follow-up contrasts); Repeated measures ANOVA; Introduction to: Canonical correlation; Discriminant function analysis, MANOVA (including for longitudinal data)

  • HD FS 526 Measurement in Human Development

    • Item response theory; Measurement validity (definitions, interpretations); Writing survey questions; Principal Components Analysis; Exploratory Factor Analysis; Confirmatory Factor analysis

  • HD FS 597E Introduction to Data Mining for Human Development

    • Introduction to data mining and machine learning techniques for analyzing moderate-to-large-scale data; Data-driven techniques for automated clustering, classification, prediction, and pattern detection, with a focus on longitudinal and highly multivariate data

  • CAS 563 Pairs & Pairings: Quantitative Methods for Interdependent Data

    • Dyadic (t-tests, Actor-Partner Interdependence Model) and social network analysis (one- and two-mode data, single time point analysis using UCINET and NetDraw)

Nutrition Minor

  • NUTR 497F Macronutrient Metabolism for Non-Nutrition Majors

  • NUTR 452 Nutritional Aspects of Disease

  • NUTR 520 Readings in Nutrition

  • NUTR / HD FS 532 Childhood Obesity

  • NUTR / HD FS 533 Adult Obesity

  • NUTR / FD SC 534 Readings in Ingestive Behavior

Information Sciences & Technology Coursework

  • IST 541 Qualitative Research in Information Sciences and Technology

    • Methods for collecting and analyzing qualitative data that informs the study of technology and computer-mediated social processes

  • IST 597B Visualization and Advanced Analysis of Social Networks

    • UCINET, Pnet, Gephi

  • IST 597D Big Data Fundamentals

    • Introduction to storage of big data (e.g., Hadoop distributed file systems, Amazon web services) the architecture for processing big data (e.g., Hash table, NoSQL); the algorithms designed (or modified) for big data processing (e.g., MapReduce, latent dirichlet allocation)

  • IST 596 Independent Study: Network analysis in R

  • IST 597I Advanced Topics on Social Network Analysis and Social Media Analytics

    • Conceptual overview of research methods that use social network and media data (e.g., small world theory, discovering influential nodes, inferring node attributes, recommendation systems, Granger causality)