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 Multivariate Multivariate: Multivariate refers to a dataset or analysis that considers more than one variable at a time. For example, in a multivariate analysis, you might examine the relationship between height and weight in order to understand how they are related. How is Multivariate used? Multivariate analysis is a collection of techniques used…
Definition of Kernel Density Estimation Kernel Density Estimation: Kernel density estimation is a technique used to estimate the probability density function of a random variable. It is often used to smooth out noisy data or in cases where the exact distribution of the data is unknown. How is Kernel Density Estimation used? Kernel Density Estimation…
Definition of Kernel Kernel: A kernel is a mathematical function that takes two inputs, typically vectors in a high-dimensional space, and outputs a scalar. The kernel function defines a similarity or distance between the two vectors. How is Kernel used? Kernel is the core component of a computer’s operating system that acts as an interface…
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 Mutation Mutation: A mutation in data science is an alteration of the data, which can be intentional or accidental. How is Mutation used? Mutation is a term that is used when talking about machine learning algorithms, particularly genetic algorithms. It refers to a process of randomly making changes or modifications to the data…
Definition of Kappa Statistic Kappa Statistic: Kappa statistic is a statistic used in machine learning and data science that measures the agreement between predicted values and observed values. Kappa statistic is calculated as the average of the absolute agreements (predicting the correct class) minus the average of the absolute disagreements (predicting the wrong class). How…