12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Markov chains are a mathematical approach used to model random behavior. They are often used to simulate random processes based not only on the current situation, but also on previous events. They use probability distributions to predict how likely certain events are. This technique is commonly used in fields such as natural sciences, finance, artificial intelligence and data analysis.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
A random sample is a selection method in which a group of elements from a given population is selected based on randomness. Each element in the population has an equal probability of being included in the sample, and each element that is selected is considered part of the sample. This method is often used in research and statistical analysis to obtain a representative group that may not be obtained by other selection methods.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Exploratory data analysis, also called exploratory data analytics or exploratory data mining, is a method for systematically exploring and processing data to gain new knowledge and insights. It is an iterative process that allows the researcher to form hypotheses, identify patterns and relationships, and understand how data is related and how it impacts new findings and insights.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
The chi-square test (also chi-square test or chi-square test) is a statistical test used to test hypotheses about the independence of two characteristics. It is often used to test the significance of an observational or experimental data analysis. The chi-square test is used to find out whether a particular set of observations or measurements is significantly different from the expected value. The test is based on comparing the empirical probabilities of a particular outcome with the theoretical probability of the same outcome.
12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Multivariate analysis is a method of statistical analysis that examines multiple variables simultaneously to identify relationships. It is commonly used in the fields of economics, psychology, sociology, and other social sciences to examine complex relationships among multiple variables. Multivariate analysis allows scientists, businesses, and organizations to identify patterns and influences that help them understand and predict behaviors and trends.