When there is a perfect linear relationship between response variable and predictor variable the predicted value will be same as true value.
That is when slope is +1 or -1 and intercept is zero.
In such cases:
The regression of Y on X be the same as regression of X on Y.
ie Y=X (Y=-X) and/ or X=Y (X=-Y)
Under what circumstances will the predicted value be the same as the true value? Or put another way when will the regre...
A trader buys a European call option and sells a European put option. The options have the same underlying asset, strike price, and maturity. Describe the trader’s position. Under what circumstances does the price of the call equal the price of the put?
In a simple regression model, the slope (b1) represents predicted value of Y when X = 0. change in estimated Y per unit change in X. predicted value of Y. variation around the sample regression line.
3. Under what circumstances can internally generated goodwill be recognized? a. When the market value of an entity exceeds b. The brand of an entity is well-respected c. The goodwill results from a contractural right d. The goodwill will result in future economic benefits e. Internally generated goodwill cannot be recognized 4. Which of the following statements is true regarding the revaluation method? a. Revaluations are always recognized in profit and loss b. Upward revaluations can never be recognized in...
27. The slope (bi) represents a) predicted value of Y, when X=0. b) the estimated average change in Y per unit change in X c) the predicted value of Y. d) variation around the line of regression
You run a regression analysis on a bivariate set of data (n=87n=87). You obtain the regression equationy=−3.815x+47.575y=-3.815x+47.575with a correlation coefficient of r=−0.349r=-0.349 (which is significant at α=0.01α=0.01). You want to predict what value (on average) for the explanatory variable will give you a value of 160 on the response variable.What is the predicted explanatory value?x = (Report answer accurate to one decimal place.)
The slope is the a. change in the predicted value of y per unit increase in x b. predicted value of y c. predicted value of y when x=0 d. smallest value for the residual sum of squares e. point where the regression line crosses the y-axis
Under what circumstances would the most probable selling price of a property and its market value be essentially the same? Under what circumstances might they differ significantly?
Given that the equation of a regression line is y^=-3.5x+4.7, what is the best predicted value for y given that x = -1.7? Assume that the variables x and y have a significant correlation.
The line of best fit through a set of data isy=−28.768+1.521xy=-28.768+1.521xAccording to this equation, what is the predicted value of the dependent variable when the independent variable has value 90?y = Round to 1 decimal place.