Key Points Non-parametric tests are used when standard assumptions are not available. These tests don’t rely on distributions ...

Several methods for RNAi HTS data analysis have been developed specifically with these issues in mind. The statistical methods outlined here, while certainly not comprehensive, offer effective ...

A new publication by two University of Cincinnati researchers contends that adjusting how researchers approach their ...

Id: 038569 Credits Min: 3 Credits Max: 3 Description. This course introduces statistical methods and techniques for multivariate data analysis. The course studies basic ideas underlying multivariate ...

In this paper, we describe modern statistical methods for presentation of the results of studies of bone marrow transplantation. We focus here on ‘univariate’ or unadjusted techniques to ...

This course covers most frequently used statistical methods for data analysis. In addition to the standard inference methods such as parameter estimation, hypothesis testing, linear models and ...

Machine Learning Algorithms: Advanced statistical methods, such as decision trees, random forests, and neural networks, used to predict outcomes based on input data. 4. Multivariate Analysis ...

SDS 390cd Topics in Statistical and Data Sciences-Categorical Data Analysis (4 Credits) Theory and applications of statistical methods for the analysis of categorical data. The course includes an ...

Statistical analysis - this aspect of quantitative analysis involves examining data to identify trends and relationships, build predictive models, and make forecasts. Techniques used can include ...