The thesis "Analysis of Contingency Tables" by James Joseph Biundo, submitted to Utah State University in 1963, focuses on the analysis of multi-dimensional frequency data using two primary methods: the Second Order Exponential (SOE) model and an Information Theoretic Approach. The SOE model is applicable for dichotomous classifications and is described by a set of parameters θi and θij, where θi represents the log of the odds of marginal probabilities if no two-factor relationships exist, and θij measures the direction and strength of two-factor relationships. The Information Theoretic Approach assumes a multinomial distribution and uses the minimum discrimination information statistic (m.d.i.s.) to test hypotheses, estimating unique cell probabilities iteratively. The thesis includes detailed mathematical formulations, interpretations of the parameters, and examples to illustrate the application of these methods. It also discusses the limitations and challenges, such as the computational complexity and the need for large sample sizes. The author emphasizes the importance of understanding the methods and their interpretations, providing a comprehensive guide for researchers in various fields who need to analyze frequency data.The thesis "Analysis of Contingency Tables" by James Joseph Biundo, submitted to Utah State University in 1963, focuses on the analysis of multi-dimensional frequency data using two primary methods: the Second Order Exponential (SOE) model and an Information Theoretic Approach. The SOE model is applicable for dichotomous classifications and is described by a set of parameters θi and θij, where θi represents the log of the odds of marginal probabilities if no two-factor relationships exist, and θij measures the direction and strength of two-factor relationships. The Information Theoretic Approach assumes a multinomial distribution and uses the minimum discrimination information statistic (m.d.i.s.) to test hypotheses, estimating unique cell probabilities iteratively. The thesis includes detailed mathematical formulations, interpretations of the parameters, and examples to illustrate the application of these methods. It also discusses the limitations and challenges, such as the computational complexity and the need for large sample sizes. The author emphasizes the importance of understanding the methods and their interpretations, providing a comprehensive guide for researchers in various fields who need to analyze frequency data.