Type I Error
Definition of Type I Error
Type I error: A type I error, also known as a false positive error, is the incorrect rejection of a true null hypothesis.
Type I error: A type I error, also known as a false positive error, is the incorrect rejection of a true null hypothesis.
Definition of Univariate Univariate: A univariate analysis is a data analysis technique that considers only one variable at a time.
Definition of Exploratory Data Analysis Exploratory Data Analysis: Exploratory data analysis (EDA) is the examination of data to summarize, visualize, and discover patterns. EDA is used to identify which variables are important and to develop hypotheses about the relationships between variables. What is an Exploratory Data Analysis used for? An Exploratory Data Analysis (EDA) is…
Definition of Type II Error Type II error: A type II error, also known as a false negative error, is the incorrect acceptance of a false null hypothesis.
Definition of Zero-Sum Game Zero-Sum Game: In game theory, a zero-sum game is a mathematical model of a situation in which each participant’s gain or loss of utility is exactly balanced by the losses or gains of the other participants. If the total gains from the interactions of all participants are net zero change, then…
Definition of Null Hypothesis The null hypothesis is a statement that is presumed to be true until evidence is presented to suggest otherwise. In statistics, the null hypothesis is typically contrasted with the alternative hypothesis, which is the statement that is posited if the null hypothesis is found to be false. The null hypothesis is…
Definition of K-means clustering K-means clustering: K-means clustering is a data mining algorithm used to partition a set of data points into k clusters. Data is divided into clusters based on the similarities of the points within each cluster. This algorithm is often used to segment customers into different groups for marketing purposes. How is…