To find the y-intercept, you need to calculate the gradient, b. Then a, the y-intercept, satisfies the equation
y-bar = a + b*x-bar
where x-bar and y-bar are the means of the two variables.
520
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.
To find the y-intercept in a table, look for the row where the x-value is zero. The corresponding y-value in that row represents the y-intercept of the function. If there is no row with an x-value of zero, the y-intercept cannot be determined from the table.
No, the graph of a polynomial function cannot have no y-intercept. A polynomial function is defined for all real numbers, and when you evaluate it at (x = 0), you get the y-intercept, which is the value of the function at that point. Thus, every polynomial function will intersect the y-axis at least once, ensuring it has a y-intercept.
y intercept is value of y when x = 0 x intercept is value of x when y = 0 if y intercept is twice x intercept then its value is twice as high Mathematically, the standard form equation is y = mx + b where m = slope and b = y intercept for x intercept let y = 0 0 = mx + b x = -b/m = 1/2 y intercept = 1/2 time b m = -2 y = -2x + b is the equation
520
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.
y must have a value of 0 at the x-intercept.
0
The parameter is the value computed, in statistics. The x and y intercept value is where the line crosses the axis.
To find the y-intercept in a table, look for the row where the x-value is zero. The corresponding y-value in that row represents the y-intercept of the function. If there is no row with an x-value of zero, the y-intercept cannot be determined from the table.
No, the graph of a polynomial function cannot have no y-intercept. A polynomial function is defined for all real numbers, and when you evaluate it at (x = 0), you get the y-intercept, which is the value of the function at that point. Thus, every polynomial function will intersect the y-axis at least once, ensuring it has a y-intercept.
Add 8 to the x value, so f.e. If x=4, the y intercept = 4+8 =12 No, the y intercept is the value of y when the value of x = 0, so the y intercept of the equation is 8. In the general form y = mx + b, b will always be the y intercept.
Suppose you have two variables X and Y, and a set of paired values for them. You can draw a line in the xy-plane: say y = ax + b. For each point, the residual is defined as the observed value y minus the fitted value: that is, the vertical distance between the observed and expected values. The least squares regression line is the line which minimises the sum of the squares of all the residuals.
y intercept is value of y when x = 0 x intercept is value of x when y = 0 if y intercept is twice x intercept then its value is twice as high Mathematically, the standard form equation is y = mx + b where m = slope and b = y intercept for x intercept let y = 0 0 = mx + b x = -b/m = 1/2 y intercept = 1/2 time b m = -2 y = -2x + b is the equation
The value of m is the slope and the value of b is the y intercept.
To find the y-intercept of a line with a given slope and a point it passes through, you can use the slope-intercept form of a line, which is (y = mx + b), where (m) is the slope and (b) is the y-intercept. Substitute the coordinates of the given point and the slope into the equation to solve for (b). Rearranging the equation will yield the value of the y-intercept. Without specific numerical values for the slope and point, I can't provide a numerical answer, but this is the method to find it.