12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Media analysis is a field of research that deals with the systematic study of media content. This includes the study of texts, images, videos, and audio files to examine the way they are used to convey messages. This also includes examining the effect that such media have on people, such as shaping opinions, ways of thinking, and behaviors. Media analysis can also help measure and evaluate the effectiveness of advertising campaigns.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Market research is the systematic collection, analysis and interpretation of information about a particular market, industry or product or service. Market research can help companies develop new products and services by gathering information about consumer needs and wants. It can also help strengthen the company's competitiveness by providing information about the competitive landscape.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Causal analysis is a method used to investigate what factors led to certain outcomes. It is a method used to identify possible causes of a particular outcome and then examine the relationship between the causes and the outcome. It is often used in research to examine relationships between variables to understand why certain events or outcomes occur.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
A Bayes network is a special type of probabilistic graph that represents the probability of certain events with respect to other events. It is commonly used in machine learning research and machine learning to model a variety of problems, such as classification, prediction, and structuring of data. It consists of nodes, which represent events, and edges, which represent the relationships between them. A Bayes network can be used to model a set of relationships between events.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Structural equation modeling (SEM) is a modern form of statistical analysis used to study relationships between variables in complex data sets. This method allows researchers to create a model that describes the influence of different variables on the behavior of an individual or group. SEM can be used to improve research results by testing hypotheses about relationships between variables, considering multiple variables simultaneously.