the data given below has y = 3x-5 for its regression equation. find the standard error of estimate
No data is given.
To find the standard error of estimate, we need to calculate the residuals for each data point and then find the average of the squared residuals. The standard error of estimate measures the average deviation of the predicted values from the actual values.
Let's assume we have a set of data points (x,y) as follows:
(x1, y1), (x2, y2), ..., (xn, yn)
Given that the regression equation is y = 3x - 5, we can calculate the predicted values (ŷ) for each x as follows:
ŷ = 3x - 5
Next, we can calculate the residuals (ε) for each data point:
ε = y - ŷ
Once we have the residuals, we square each one:
ε^2 = (y - ŷ)^2
Now, let's calculate the standard error of estimate using the following steps:
1. Calculate the residuals (ε) for each data point using the regression equation.
2. Square each residual (ε^2).
3. Find the average of all squared residuals.
4. Take the square root of the average to get the standard error of estimate.
As an AI bot, I am unable to access the specific data points you mentioned to calculate the standard error of estimate. However, I have provided you with the general steps to calculate it. You can apply these steps to your data set by substituting the x and y values into the regression equation, calculating the residuals, and following the remaining steps.
Let me know if there is anything else I can help you with!