Mathematical Models of Solute Retention in Gas Chromatography
... Table III and compared with data taken from the literature and with those extrapolated by the use of linear regression, which relates the enthalpy of vaporization with the number of carbon atoms in the molecule of the analyte (as denoted by the italics). This comparison gives evidence that the model ...
... Table III and compared with data taken from the literature and with those extrapolated by the use of linear regression, which relates the enthalpy of vaporization with the number of carbon atoms in the molecule of the analyte (as denoted by the italics). This comparison gives evidence that the model ...
Trade Facilitation and Country Size
... across countries in the past. However, our regression results could suffer from omitted variable bias problem. To guard against this possibility, we use a number of controls informed by the broader literature on trade openness and country size. As a further check against the omitted variable bias pr ...
... across countries in the past. However, our regression results could suffer from omitted variable bias problem. To guard against this possibility, we use a number of controls informed by the broader literature on trade openness and country size. As a further check against the omitted variable bias pr ...
The Law of Cosines
... Notice that the letter of the side that is being calculated only appears once in the formula and that is for its corresponding angle. The remainder of the formula consists of the letters of the other two sides – the sum of their squares minus twice their product times the cosine of the included angl ...
... Notice that the letter of the side that is being calculated only appears once in the formula and that is for its corresponding angle. The remainder of the formula consists of the letters of the other two sides – the sum of their squares minus twice their product times the cosine of the included angl ...
Statistical Methods in Meteorology - Time Series Analysis
... A single ramp function would not provide an quate model for this data. This can be seen dir from Fig. 16 and would also be revealed by resi analysis. Instead we ®t two ramps, the older trans corresponding to initial, strong cooling, the younge the following, minor warming (Fig. 16, Table 2). sidual ...
... A single ramp function would not provide an quate model for this data. This can be seen dir from Fig. 16 and would also be revealed by resi analysis. Instead we ®t two ramps, the older trans corresponding to initial, strong cooling, the younge the following, minor warming (Fig. 16, Table 2). sidual ...
Simultaneous equations regression model
... A simultaneous equation regression model has two alternative specifications: reduced form and structural form. The reduced-form specification is comprised of M reduced-form equations and a set of assumptions about the error terms in the reduced form equations. The reduced-form specification of the m ...
... A simultaneous equation regression model has two alternative specifications: reduced form and structural form. The reduced-form specification is comprised of M reduced-form equations and a set of assumptions about the error terms in the reduced form equations. The reduced-form specification of the m ...
x - College of Business « UNT
... 87.2 % R2 for the no-log model is the percentage of variation in Imports explained. The 84.0% for the second model is the percentage of variation in ln(Imports) explained. If you converted the fitted values of the second model back to Imports you might find the log model better. Fitting Curves t ...
... 87.2 % R2 for the no-log model is the percentage of variation in Imports explained. The 84.0% for the second model is the percentage of variation in ln(Imports) explained. If you converted the fitted values of the second model back to Imports you might find the log model better. Fitting Curves t ...
Coefficient of determination
In statistics, the coefficient of determination, denoted R2 or r2 and pronounced R squared, is a number that indicates how well data fit a statistical model – sometimes simply a line or a curve. An R2 of 1 indicates that the regression line perfectly fits the data, while an R2 of 0 indicates that the line does not fit the data at all. This latter can be because the data is utterly non-linear, or because it is random.It is a statistic used in the context of statistical models whose main purpose is either the prediction of future outcomes or the testing of hypotheses, on the basis of other related information. It provides a measure of how well observed outcomes are replicated by the model, as the proportion of total variation of outcomes explained by the model (pp. 187, 287).There are several definitions of R2 that are only sometimes equivalent. One class of such cases includes that of simple linear regression where r2 is used instead of R2. In this case, if an intercept is included, then r2 is simply the square of the sample correlation coefficient (i.e., r) between the outcomes and their predicted values. If additional explanators are included, R2 is the square of the coefficient of multiple correlation. In both such cases, the coefficient of determination ranges from 0 to 1.Important cases where the computational definition of R2 can yield negative values, depending on the definition used, arise where the predictions that are being compared to the corresponding outcomes have not been derived from a model-fitting procedure using those data, and where linear regression is conducted without including an intercept. Additionally, negative values of R2 may occur when fitting non-linear functions to data. In cases where negative values arise, the mean of the data provides a better fit to the outcomes than do the fitted function values, according to this particular criterion.