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What is better high-low method or least squares regression better?
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What is weighted residual method?
In estimating a linear relationship using ordinary least squares (OLS), the regression estimates are such that the sums of squares of the residuals are minimised. This method treats all residuals as being as important as others.There may be reasons why the treatment of all residuals in the same way may not be appropriate. One possibility is that there is reason to believe that there is a systematic trend in the size of the error term (residual). One way to compensate for such heteroscedasticity is to give less weight to the residual when the residual is expected to be larger. So, in the regression calculations, rather than minimise the sum of squares of the residuals, what is minimised is their weighted sum of squares.
What is another name for regression method?
time series
What is Least Cubic Method?
"Least Cubic Method" Also called "Generalized the Least Square Method", is new Method of data regression.
Is it possible for you to use trial and error method or the X-method to factor the difference of two squares?
No it is not. At least, not sensibly.
How do you calculate a straight line in statistics?
The method used to calculated the best straight line through a set of data is called linear regression. It is also called the least squares method. I've included two links. I know the wikipedia link is a bit complicated. The slope and intercept are calculated based on "minimum least squares." If I draw a line through the set if points, for every x value in the data set I will have a y value and a predicted y value (y-hat) based on the straight line. The error (E) is this case is the predicted y minus the actual y. Linear regression finds the slope and intercept of the equation that minimizes the sum of the square of the errors. Mathematically this is stated as: Min z = sum (yi - y-hat)^2 To hand calculate a linear regression line wold take some time. The second link that I've included shows how to calculated this using excel.
Why are there two regression lines?
There are two regression lines if there are two variables - one line for the regression of the first variable on the second and another line for the regression of the second variable on the first. If there are n variables you can have n*(n-1) regression lines. With the least squares method, the first of two line focuses on the vertical distance between the points and the regression line whereas the second focuses on the horizontal distances.
Is the high-low method less accurate than the least-squares regression method for analyzing the behavior of mixed cost?
The fact that the high-low method uses only two data points is a major defect of the method.
What is weighted residual method?
In estimating a linear relationship using ordinary least squares (OLS), the regression estimates are such that the sums of squares of the residuals are minimised. This method treats all residuals as being as important as others.There may be reasons why the treatment of all residuals in the same way may not be appropriate. One possibility is that there is reason to believe that there is a systematic trend in the size of the error term (residual). One way to compensate for such heteroscedasticity is to give less weight to the residual when the residual is expected to be larger. So, in the regression calculations, rather than minimise the sum of squares of the residuals, what is minimised is their weighted sum of squares.
What regression method would be used when there is more than one independent variable?
multivariate regression
What is another name for regression method?
time series
What is the formula of scatter graph method?
I believe it is linear regression.
What is Least Cubic Method?
"Least Cubic Method" Also called "Generalized the Least Square Method", is new Method of data regression.
Is the line of best fit the same as linear regression?
Linear Regression is a method to generate a "Line of Best fit" yes you can use it, but it depends on the data as to accuracy, standard deviation, etc. there are other types of regression like polynomial regression.
The multiple regression statistical method is used to examine what relationship?
The multiple regression statistical method examines the relationship of one dependent variable (usually represented by 'Y') and one independent variable (represented by 'X').
What is the name of the method for drawing a trend line for the data in a scatterplot?
There are many methods, though the most popular is the method of least squares. This method minimises the sum of the squares of the vertical distances between each point and the corresponding point on the line.
How do you calculate fixed cost and variable cost given total cost and quantity?
We can calculate using following methods 1 - High-Low method 2 - Regression analysis method 3 - Graphical method
Which is found in the last step of the least-squares method?
nuckets
