Mathematical techniques for trying to understand why things are getting worse.
A statistical technique for determining the constant and coefficients in a multi-variate targeting model of the form: E = k0 + k1.D1 + k2.D2 + ... + kn.Dn (more)
An evaluation of the long-term hoop stress data. A linear curve is calculated using the least Squares method to fit the logarithm of hoop stress versus the logarithm of the resulting hours-to-failure.
The representation of a variable by a regression function.
A statistical inference technique which can be used to establish the significance of any correlation (association) between variables of interest, e.g. the gender of a long-term unemployed worker and the amount of time before he or she finds a new job after a training programme. In regression analysis, we attempt to establish whether the variation in one variable (known as the dependent variable) can be explained in terms of the variation in one or more independent variables. The dependent variable is often quantitative, e.g. a person's income can be regressed on his educational qualifications, number of hours worked per week, age, etc. Special techniques are available, however, to deal with situations in which the dependent variable is qualitative, e.g. whether or not a person owns a car can be regressed on income, wealth, age, gender etc. See also statistical analysis.
The method of estimating relationships between dependent variables and one or more independent variables that measures how the distribution of a variable changes as input conditions are changed.
The statistical technique of finding a straight line that approximates the information in a group of data points. Used throughout empirical economics, including in both international trade and finance.
A statistical technique designed to characterise the relationship between changes in some factor (e.g., concentration of a pollutant) and a biological response (e.g., narrowing of the airways)
Analysis of the mathematical relationship between two variables.
A way of predicting one value/amount (the “effect” or “dependent variable”) from other values/amounts (the “causes” or “independent variables”); predicting the effect by what the cause looks like.
Statistical tool used to make a quantitative estimation of the influence of several explanatory variables (public intervention and confounding factors) on an explained variable (an impact). Regression analysis is a tool for analysing deductive causality. It is based on an explanatory logical model and on a series of preliminary observations. The tool can be used in varying ways, depending on whether the variables of the model are continuous or discrete and on whether their relations are linear or not. BACK
a statistical process for fitting a line through a set of data points. It gives the intercept and slope(s) of the “best fitting” line. Thus it tells how much one variable (the dependent variable) will change when other variables (the independent, or explanatory, variables) change.
A statistical measure used to discover relationships between variables such as performance ratings and promotions.
an analysis of the nature of the relationship between two or more variables, expressed as a mathematical function. On a scatter plot, this relationship is diagrammed as a line drawn through data points. A straight line indicates simple regression; a curve indicates a higher-order regression.
Measurement of the change in one variable as a result of changes in one or more variables. Regression analysis is used frequently in an attempt to identify the variables that affect a certain stock's price.
Modeling method that takes into account historical and demographic variables and relies on statistical calculations to weigh the variables. Certain standard industrial classifications (SICs), for instance, might be assigned a higher value than others; household income might be factored by a number so that wealthier buyers are ranked as proportionately more valuable than less-wealthy customers.
A statistical technique to derive an equation that relates a single, continuous criterion variable to one or more continuous predictor variables.
A process of forecasting which involves taking one or more known variables to forecast an unknown variable, such as sales, based on the values of the known variables. Regression analysis generates a trend line, called a Regression Line(def) is where all the forecasted values lie.
A statistical tool used to compare the performance of a school to those that are demographically similar. When we say that a value was â€œtaken into consideration in the regression,â€ it was used as one of the comparison tools.
Statistical technique used to measure the association among two or more variables.
a fundamental and versatile research technique that seeks to explain an outcome (dependent) variable in terms of multiple predictor (independent) variables. This analysis reveals the nature and strength of the relationship between each predictor variable and the outcome, independent of the influence from all other predictors. The term typically refers to Ordinary Least Squares (OLS) regression, which models a linear relationship among variables.
Concerned with measuring the way in which one variable is related to another. The purpose is to predict the value of a continuous variable using other independent variables.
Where past data is insufficient for direct forecasting of future levels of activity it may still be possible to make assumptions base d on relationship s with other activities that can be forecast. This applies part icularly to apportioned-effort task s and to a lesser extent to level-of-effort task [D03084] CCCP quantitative technique used to establish a line-of-best-fit through a set of data to establish a relationship between one or more independent variable and a dependent variable. That line is then used with a project ed value of the independent variable(s) to estimate value for the dependent variable. Editor's Note: A valuable estimating tool provided the value to be estimate lies within the observed data and not beyond those limits. [D03558] GAT
A statistical technique for determining the best mathematical expression describing the functional relationship between one response and one or more independent variables. See: least-squares method.
A set of statistical operations that help to predict the value of the dependent variable from the values of one or more independent variables.
A method of determining relationships among different data in order to predict future behavior/results
A statistical technique used to measure the impact (eg. on a share price) of a change in one or more variable factors.
A statistical technique used to find relationships between variables for the purpose of predicting their future values
A statistical technique applied to data to determine, for predictive purposes, the degree of correlation of a dependent variable with one or more independent variables, in other words, to see if there is a strong or weak cause and effect relationship between to things. See least-squares fit.
A statistical method that estimates any trend that might exist among important factors. An example in fisheries management is the link between catch and other factors like fishing effort and natural mortality.
A method for determining the association between a dependent variable and one or more independent variables.
is a mathematical procedure which is used to determine and measure the predictive relationship between one variable (dependent variable) and one or more other variables (independent variables). (420.01.1h)
A statistical technique that can be used to estimate relationships between variables.
Analysis that is used to depict the relation between dependent and independent variables derived from a study. The goal of regression is to find a mathematical model that best explains how changes in the independent predictor variables affect the dependent response variables. A fitted regression model estimates the relation between predictors and responses and may be used to forecast or predict values of the responses.
The use of regression to make quantitative predictions of one variable from the values of another.
A statistical technique for investigating and modeling the relationship between variables.
A statistical means to improve the predictability of response based on an analysis of multiple, stratified relationships within a file.
A statistical technique used to determine the best mathematical expression to describe the relationship between a response and independent variables.
A statistical measure used to analyse the impact of change in one or more variable factors of a share price.
A statistical method of determining, or predicting, the value of a dependent variable, based on levels of one or more know independent variables.
A statistical technique used in modern stock portfolio analysis to compare returns on a particular stock or particular portfolio of stocks with the returns for a larger group of stocks or an index of stocks. The slope of the resulting regression line is called the Beta and it quantifies the stock's or the particular portfolio's sensitivity to systematic risk.
A statistical technique that establishes the best linear relationship between two or more quantifiable variables to be predicted from one or more independent or explanatory variables.
The association of one or more independent variables with a dependant variable. The relationships are associative only; causative inferences are added subjectively by the analysts. Cost Estimators Reference Manual, Stewart, Wyskida & Johannes, Second Edition Keyword(s): Regression Analysis
In statistics, regression analysis is the process used to estimate the parameter values of a function, in which the function predicts the value of a response variable in terms of the values of other variables. There are many methods developed to fit functions and these methods typically depend on the type of function being used. For example: linear regression, nonlinear regression, and logistic regression.