In descriptive statistics, summary statistics are used to summarize a set of observations, in order to communicate the largest amount of information as simply as possible. Statisticians commonly try to describe the observations in
In statistics, correlation or dependence is any statistical relationship, whether causal or not, between two random variables or bivariate data. Although in the broadest sense, "correlation" may indicate any type of association, in statistics it usually refers to the degree to which a pair of variables are linearly related. Familiar examples of dependent phenomena include the correlation between the height of parents and their offspring, and the correlation between the price of a good and the quantity the consumers are willing to purchase, as it is depicted in the so-called demand curve.
In statistics, the Pearson correlation coefficient (PCC) is a correlation coefficient that measures linear correlation between two sets of data. It is the ratio between the covariance of two variables and the product of their standard deviations; thus, it is essentially a normalized measurement of the covariance, such that the result always has a value between −1 and 1. As with covariance itself, the measure can only reflect a linear correlation of variables, and ignores many other types of relationships or correlations. As a simple example, one would expect the age and height of a sample of teenagers from a high school to have a Pearson correlation coefficient significantly greater than 0, but less than 1.
In statistics, Spearman's rank correlation coefficient or Spearman's ρ, named after Charles Spearman and often denoted by the Greek letter (rho) or as , is a nonparametric measure of rank correlation. It assesses how well the relationship between two variables can be described using a monotonic function.
In mathematics, a time series is a series of data points indexed in time order. Most commonly, a time series is a sequence taken at successive equally spaced points in time. Thus it is a sequence of discrete-time data. Examples of time series are heights of ocean tides, counts of sunspots, and the daily closing value of the Dow Jones Industrial Average.
In education, a curriculum is broadly defined as the totality of student experiences that occur in the educational process. The term often refers specifically to a planned sequence of instruction, or to a view of the student's experiences in terms of the educator's or school's instructional goals. A curriculum may incorporate the planned interaction of pupils with instructional content, materials, resources, and processes for evaluating the attainment of educational objectives. Curricula are split into several categories: the explicit, the implicit, the excluded, and the extracurricular.
In the field of machine learning and specifically the problem of statistical classification, a confusion matrix, also known as error matrix, is a specific table layout that allows visualization of the performance of an algorithm, typically a supervised learning one; in unsupervised learning it is usually called a matching matrix.
In statistics, a contingency table is a type of table in a matrix format that displays the multivariate frequency distribution of the variables. They are heavily used in survey research, business intelligence, engineering, and scientific research. They provide a basic picture of the interrelation between two variables and can help find interactions between them. The term contingency table was first used by Karl Pearson in "On the Theory of Contingency and Its Relation to Association and Normal Correlation", part of the Drapers' Company Research Memoirs Biometric Series I published in 1904.
In statistics, the coefficient of multiple correlation is a measure of how well a given variable can be predicted using a linear function of a set of other variables. It is the correlation between the variable's values and the best predictions that can be computed linearly from the predictive variables.
In statistics, the coefficient of determination, denoted R2 or r2 and pronounced "R squared", is the proportion of the variation in the dependent variable that is predictable from the independent variable(s).
In fluorescence microscopy, colocalization refers to observation of the spatial overlap between two different fluorescent labels, each having a separate emission wavelength, to see if the different "targets" are located in the same area of the cell or very near to one another. The definition can be split into two different phenomena, co-occurrence, which refers to the presence of two fluorophores in the same pixel, and correlation, a much more significant statistical relationship between the fluorophores indicative of a biological interaction. This technique is important to many cell biological and physiological studies during the demonstration of a relationship between pairs of bio-molecules.
Saint Francis School is a Private, Independent, not for profit, college preparatory school with no religious affiliation that has been serving students of the Metro Atlanta area since 1976. Saint Francis School is accredited by the Georgia Accrediting Commission (GAC), the Southern Association of Independent Schools (SAIS), and the Southern Association of Colleges and Schools (SACS). It is a member of Georgia Independent School Association (GISA) and the Atlanta Area Association of Independent Schools (AAAIS).
In statistics, inter-rater reliability is the degree of agreement among independent observers who rate, code, or assess the same phenomenon.
A hydrologic model is a simplification of a real-world system that aids in understanding, predicting, and managing water resources. Both the flow and quality of water are commonly studied using hydrologic models.
The Robert Day School of Economics and Finance (RDS) at Claremont McKenna College is an economics school, and the only graduate program at Claremont McKenna College. The Robert Day School emphasizes coursework that blends theory and practice. The undergraduate programs offer majors in economics and economics-accounting, and a sequence in financial economics. RDS also offers a specialized full-time master's degree in finance as well as administering the Robert Day Scholars Program. In contrast to any other liberal arts college, the offerings include a broad spectrum of core and elective courses in finance and accounting. The course is designed to develop the individual student's analytical, quantitative, and communication skills.
In statistics, the RV coefficient is a multivariate generalization of the squared Pearson correlation coefficient. It measures the closeness of two set of points that may each be represented in a matrix.
In statistics, the phi coefficient is a measure of association for two binary variables.
A correlation coefficient is a numerical measure of some type of correlation, meaning a statistical relationship between two variables. The variables may be two columns of a given data set of observations, often called a sample, or two components of a multivariate random variable with a known distribution.
Bivariate analysis is one of the simplest forms of quantitative (statistical) analysis. It involves the analysis of two variables, for the purpose of determining the empirical relationship between them.
A gene co-expression network (GCN) is an undirected graph, where each node corresponds to a gene, and a pair of nodes is connected with an edge if there is a significant co-expression relationship between them. Having gene expression profiles of a number of genes for several samples or experimental conditions, a gene co-expression network can be constructed by looking for pairs of genes which show a similar expression pattern across samples, since the transcript levels of two co-expressed genes rise and fall together across samples. Gene co-expression networks are of biological interest since co-expressed genes are controlled by the same transcriptional regulatory program, functionally related, or members of the same pathway or protein complex.
