A hypothesis is broadly described as a proposition expressing a belief about the world. This proposition defines certain expectations regarding observations, associations and causal relationships, based on previous empirical results, interventions or conclusions.
Formulating a hypothesis is one of the most relevant steps in the scientific endeavor, and as such it is not an easy task.
Hypothesis formulation requires thorough knowledge of the subject matter and its theoretical framework, as well as expertise in research methods and techniques.
e[hypothesis] is designed to facilitate the process of hypothesis generation and formulation across a wide spectrum of scientific domains, utilizing a unique application of causal analysis.
Generate and formulate novel hypotheses to test previously unexplored associations in the data that could revolutionize research and innovation
Assign a level of confidence and significance to all hypotheses, supporting both Bayesian and Frequentist approaches
Provide causal analysis given specific hypotheses and the chosen datasets
Generate causal diagrams to illustrate the current knowledge and to represent formulated hypotheses
Use the multi-layer hypergraph to explore and exploit hypothesis-driven data interactions (synergistic or anti-synergistic) and generate multi-causal explanations
Eagle Genomics’ innovative approach in establishing a platform-driven ecosystem for the generation and exchange of scientific data-derived assets is of great potential value to Unilever.
Healthy animals, healthy people and a healthy planet are all interconnected. With the advanced knowledge and insights we anticipate generating from our microbiome data, the e[datascientist] will allow us to bring more relevant products to market.
As a company driven by innovation, Reckitt collaborates with partners who bring powerful new capabilities to the table so we can deliver disruptive ideas to the market.
