Econometrics

Definition of Econometrics Econometrics is a quantitative research field in economics that uses mathematical and statistical methods to analyze economic data. What is Econometrics used for? Econometrics is an empirical branch of economics that uses statistical methods to analyze economic data and evaluate theories. It utilizes mathematical models and statistical concepts to study a variety…

Exploratory Data Analysis

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…

Expectation Maximization

Definition of Expectation Maximization Expectation Maximization: Expectation Maximization (EM): A statistical algorithm used to find the maximum likelihood estimate of a parameter in a probabilistic model. EM iteratively maximizes the expected likelihood of the data under the model, by adjusting the model’s parameters. What is Expectation Maximization used for? Expectation Maximization (EM) is a statistical…

Exact p-value

Definition of Exact p-value Exact p-value: The Exact p-value is the probability of obtaining a test statistic at least as extreme as the one that was actually observed, assuming that the null hypothesis is true. What is Exact p-value used for? Exact p-values are used to help assess the strength of evidence for a hypothesis…

Exact Match

Definition of Exact Match Exact Match: Exact match is a term used in data science to describe a type of search algorithm that compares two strings of text and determines whether or not they are an exact match. What is an Exact Match used for? An Exact Match is a type of data matching algorithm…

Evaluation

Definition of Evaluation Evaluation: Evaluation is the process of assessing how well a model or system is performing, typically by measuring its accuracy, precision, recall, or some other performance metric. Evaluation is an important part of the data science process, as it allows you to determine whether your models are meeting your expectations and helping…

Euclidean Distance

Definition of Euclidean Distance Euclidean Distance: The Euclidean distance between two points is the length of the straight line between them. What is Euclidean Distance used for? Euclidean Distance is a mathematical tool used to measure the distance between two points in a multidimensional space. It is also known as the “straight line” or “as-the-crow-flies”…

Error

Definition of Error Error: An error is an incorrect result produced by a calculation. In data science, an error is an inconsistency or inaccuracy in data. Errors can be the result of incorrect measurements, incorrect entry of data, or simply a mistake. In order to ensure the accuracy of data, it is important to identify…

Epoch

Definition of Epoch Epoch: Epoch is a term used in data science to denote a specific point in time. It may be used, for example, to indicate the beginning of a period when data is collected or the end of a period when data is analyzed. When is an Epoch used? An epoch is a…

Entropy

Definition of Entropy Entropy: Entropy is a measure of the unpredictability of a system. In information theory, entropy ( ) is a measure of the uncertainty associated with a random variable. Entropy is defined as the average amount of information that is not known about the value of a random variable. When is Entropy used?…