Search
Now showing items 1-4 of 4
Type I Error Assessment and Power Comparison of ANOVA and Zero-Inflated Methods on Zero-Inflated Data
(North Dakota State University, 2019)
Many tests for the analysis of continuous data have the underlying assumption that the data in question follows a normal distribution (ex. ANOVA, regression, etc.). Within certain research topics, it is common to end up ...
Empirical Study of Two Hypothesis Test Methods for Community Structure in Networks
(North Dakota State University, 2019)
Many real-world network data can be formulated as graphs, where a binary relation exists between nodes. One of the fundamental problems in network data analysis is community detection, clustering the nodes into different ...
Bayesian Sparse Factor Analysis of High Dimensional Gene Expression Data
(North Dakota State University, 2019)
This work closely studied fundamental techniques of Bayesian sparse Factor Analysis model - constrained Least Square regression, Bayesian Lasso regression, and some popular sparsity-inducing priors. In Appendix A, we ...
Analyzing and Controlling Biases in Student Rating of Instruction
(North Dakota State University, 2019)
Many colleges and universities have adopted the student ratings of instruction (SROI) system as one of the measures for instructional effectiveness. This study aims to establish a predictive model and address two questions ...