regression analysis

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re·gres·sion a·nal·y·sis

the statistical method of finding the "best" mathematical model to describe one variable as a function of another.

re·gres·sion a·nal·y·sis

(rĕ-greshŭn ă-nali-sis)
The statistical method of finding the "best" mathematic model to describe one variable as a function of another.

regression analysis

(in statistics) a test in which the size of one variable (the dependent variable) is dependent on another (the independent variable). Often the relationship is a linear one, enabling a line of best fit to be drawn on a SCATTER DIAGRAM.

re·gres·sion a·nal·y·sis

(rĕ-greshŭn ă-nali-sis)
The statistical method of finding the "best" mathematic model to describe one variable as a function of another.

regression analysis,

n a method of correlation for computing the most probable value of one variable,
y, from the known value of another variable,
x; a method for computing the amount of change in one variable for a unit change in another. It is spoken of as the regression of
x on
y and notated
rxy.

analysis

separation into component parts.

cohort analysis
the separation of each of two cohorts into component parts and comparing the results.
current analysis
analysis performed on contemporary data.
discriminant analysis
a form of multivariate analysis in which the objective is to establish a discriminate function. The function (typically a mathematical formula) discriminates between individuals in the population and allocates each of them to a group within the population. The function is established on the basis of a series of measurements or observations made on the individuals.
economic analysis
evaluation of the costs and benefits of a commercial enterprise that takes into account additional returns, returns no longer obtained, additional costs and costs no longer incurred, discounting of gains back to the time when the project began, and opportunity costs relating to potential profitability from alternative use of the investment.
factor analysis
a multivariate technique which analyzes the underlying structure of a set of data. It is useful in explaining observed relationships amongst a large number of variables in terms of simpler relations.
guaranteed analysis
declares the range within which nutrients occur in a manufactured animal food.
multivariate analysis
techniques for the study of simultaneous variation in a number of variables. Includes linear discriminant functions, cluster analysis and factor and principal component analysis.
path analysis
a statistical technique for testing a limited number of causal hypotheses, the causal relationships between variables, by manipulation of one or more of the variables and predicting the outcome.
qualitative analysis
determination of the nature of the constituents of a compound or mixture.
quantitative analysis
determination of the proportionate quantities of the constituents of a compound or mixture.
regression analysis
a general statistical technique that analyzes the relationship between a dependent (criterion) variable and a set of independent (predictor) variables.
systems analysis
analysis of the interaction of a system, e.g. a biological system, often for the purpose of analyzing the differences between systems. See also system.
analysis of variance
a statistical method for comparing variables by partitioning the variance of the observations between the effects of the different variables and comparing it with the underlying random variation.
vector analysis
analysis of a moving force to determine both its magnitude and its direction, e.g. analysis of the scalar electrocardiogram to determine the magnitude and direction of the electromotive force for one complete cycle of the heart.

regression

1. return to a former or earlier state.
2. subsidence of clinical signs or of a disease process.
3. in biology, the tendency in successive generations toward the mean.
4. the relationship between pairs of random variables; the mean of one variable and its location is influenced by another variable.

regression analysis
see regression analysis.
regression coefficient
is the factor which determines the slope of a regression line; the greater the coefficient the steeper the line.
curvilinear regression
when the relationship between two variables is not linear.
linear regression
the relationship between two variables is a straight line.
References in periodicals archive ?
8) In addition, three lagged models were estimated for both the logit and the OLS regressions.
The OLS regression specified in Equation 1 is illustrated in Table 3 where Column 1 shows the regression results of migrant and household characteristics as the only determinants of the (log of) remittances sent back home by the Saudi migrant, while Column 2 includes the district dummies.
Panels A and B report OLS regression results with the change in Tobin's Q and change in market-to-book value.
APPENDIX OLS Regression Results for Course Average Standard Estimate Error t Stat P- Intercept 50.
The presence of spatial autocorrelation in the data violates the independence assumption of the OLS regression and demands explicit treatment with a spatial autoregressive model.
To the extent that tort reforms have differential effects on firms with varying levels of losses, estimates from OLS regressions, which capture the effects on the average firm, may miss potentially significant influence of the reforms.
The OLS regression results indicated that holding other factors constant, non-homeowners held significantly lower levels of net worth than did homeowners among near-retirees.
Traditional hedonic modelling entails the use of OLS regression to estimate the values of characteristics falling into three categories: structural, accessibility, and neighbourhood (Fik et al 2003).
Column 1 shows the pooled OLS regression coefficients, and Columns 2-7 show the coefficients from the panel estimation with three different fixed effect specifications.
6 (1) Individuals (2) State and local governments and their retirement (3) Non-US investors (4) Depository institutions (5) Bank managed estates and trusts (6) Life insurance companies (7) Other insurance companies (8) Mutual funds (9) Closed-end funds (10) Exchange-traded funds (11) Brokers and dealers Table 4: Regression of Share Turnover on Investor Holdings OLS regression in which dependent variable, share turnover, is shares traded in the quarter divided by total shares outstanding, annualized by multiplying by the ratio of the number of trading days in the year to the number of trading days in the quarter.
The overdispersion test is based on an auxiliary OLS regression of the squared residuals minus the actual values of the dependent variable on the squared fitted values of the dependent variable (without a constant):