12/06/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Inferential statistics is an analytical procedure used to answer questions related to a population. It is used to draw conclusions about a population based on a sample. It is a form of inductive statistics in which a sample is applied to a population to make generalizations about the population. Inferential statistical techniques are commonly used in research and decision making.
12/05/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Linear regression is a simple model of statistical analysis used to predict values by establishing a linear relationship between one variable (dependent) and several other variables (independent). It involves fitting a linear equation to the observed data points to minimize the least square deviation between the observed data points and the fitted linear function.
12/05/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Logistic regression is a type of statistical modeling used to predict a binary output of an event. It is commonly used in areas such as disease risk prediction, customer satisfaction, and advertising. It is a type of regression analysis that predicts a binary outcome from a set of variables. It is typically used to determine whether or not an event will occur based on a number of influencing factors.
12/05/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Factor analysis is a statistical technique used to examine the structure of a data set. It is used to reduce the variables in a data set by grouping similar variables together to create a single variable called a factor. This allows for a better understanding of the relationships between variables. It can also be used to determine which variables contribute most to a particular outcome.
12/05/2022 | by Patrick Fischer, M.Sc., Founder & Data Scientist: FDS
Extrapolation is a statistical process that attempts to reach a conclusion about a phenomenon or data structure based on certain existing data. It is a method of forecasting based on the assumption that certain trends present in the current data will exist in the future.