Analysis of Discrete Data Assignment help and Online help

The Statistical Analysis of Discrete Data provides an introduction to cur­ rent statistical methods for analyzing discrete response data. Statisticsonlineassignmenthelp believes in not only assisting in the respective projects but also strives to make the student well versed in the  subject and making them aware of the core knowledge so that they can comprehend the assignment easily, which ultimately helps in fetching higher grades. We at Statisticsonlineassignmenthelp provide Expert Knowledge and guidance in Statistical Analysis of Discrete Data Assignments. Statisticsonlineassignmenthelp provides timely help at affordable charges with detailed answers to your Statistical Analysis of Discrete Data assignments, homework , Statistical Analysis of Discrete Data research paper writing, research critique, Statistical Analysis of Discrete Data case studies or term papers so that you get to understand your assignments better apart from having the answers. We have assisted innumerable students in the Statistical Analysis of Discrete Data project and their success has promulgated Statistical Analysis of Discrete Data service.


Here are few topics in which our Experts have already provided help to the student across the globe.

  • Structural models for discrete data in two or more dimensions
  • Generalized Linear Model for discrete data
  •  Poisson and Logistic regression models
  • Elements of inference for cross-classification tables
  • Data Analysis with computer packages
  • Mutual, Partial and Conditional Independencies
  • Conditional Models - Generalized Linear Models
  • Multinomial Discriminant Analysis
  • Multinomial Distribution : marginal and conditional distributions
  • Measures of association
  • Estimation in complete tables
  • Goodness of fit, choice of a model
  • Log-linear models
  • Models for nominal and ordinal response
  • Independance and Homogeneity
  • Logit and Probit Models
  • Measures of association and particular tests (Fisher, Mac Nemar)