Regression analysis describes the relationship between two or more variables. The measure of the explanatory power of the regression model is R2 (i.e. coefficient of determination).
The question should have been " want to measure power by 3 watt meter method" The answer is Yes it is standard method to measure the power
ratio of transmitted power and received power
A voltmeter would measure the voltage. If you measure the voltage drop over a known low resistance you get a kinda-sorta idea of the power available.
Power isn't linear - at twice the current you don't have twice the power, but four times the power.
1000v times 5.2amps.AnswerThe watt is used to measure true power. The volt ampere is used to measure apparent power. So, you cannot convert one to the other, as they measure different quantities. However, when the current and voltage are in phase with each other (i.e. having unity power factor), the apparent power will equal the true power.
There are many possible reasons. Here are some of the more common ones: The underlying relationship is not be linear. The regression has very poor predictive power (coefficient of regression close to zero). The errors are not independent, identical, normally distributed. Outliers distorting regression. Calculation error.
multiple correlation: Suppose you calculate the linear regression of a single dependent variable on more than one independent variable and that you include a mean in the linear model. The multiple correlation is analogous to the statistic that is obtainable from a linear model that includes just one independent variable. It measures the degree to which the linear model given by the linear regression is valuable as a predictor of the independent variable. For calculation details you might wish to see the wikipedia article for this statistic. partial correlation: Let's say you have a dependent variable Y and a collection of independent variables X1, X2, X3. You might for some reason be interested in the partial correlation of Y and X3. Then you would calculate the linear regression of Y on just X1 and X2. Knowing the coefficients of this linear model you would calculate the so-called residuals which would be the parts of Y unaccounted for by the model or, in other words, the differences between the Y's and the values given by b1X1 + b2X2 where b1 and b2 are the model coefficients from the regression. Now you would calculate the correlation between these residuals and the X3 values to obtain the partial correlation of X3 with Y given X1 and X2. Intuitively, we use the first regression and residual calculation to account for the explanatory power of X1 and X2. Having done that we calculate the correlation coefficient to learn whether any more explanatory power is left for X3 to 'mop up'.
yes
Predictions
jealous is used to measure power?
A watt meter will measure active power, not reactive power.
The original Jones model of non-discretionary accruals was developed by J. Jones in a 1991 paper in which she asserted that firms under the scope for import relief would engage in income-reducing earnings management. It is a cross-sectional regression model: Non-discretionary accruals = OLScoeff(1)(1/Assets) + OLScoeff(2)(chg in Rev) + OLScoeff(3)(gross PPE) + error of estimates This original model has been refined many times to include the modified-Jones model which tweaks the second factor changing it from OLScoeff(2)(chg in Rev - chg in Rcvbls) Both are among the several regression tests for earnings management but the limitation of all regression tests of EM is that (1) the power of the tests are generally low (partially explain variation if and when detected), and (2) they are all ex post measures (lagging). Additional models include the industry model and the Healy model.
indepedent variable
generator
The Watt is the unit used to measure electric power :)
Dennis Leech has written: 'Econometric evidence on LDC exports' 'Power relations in the international monetary fund' 'Power indices and probabilistic voting assumptions' 'An application of random coefficient regression' 'A note on testing the error specification in nonlinear regression' 'The relationship between shareholding concentration and shareholder voting power in British companies' 'The separation of corporate ownership and control'
Hypotheses usually are relatively narrow in scope; theories have broad explanatory power. -ahd