0
Suppose you have n objects and for each object you have observations for k+1 variables, X1, X2, ... , Xk and Y.Then a linear regression is an equation of the form E(y) = a + b1x1 + b2x2 + ... + bkxk
where E(y) is the expected value of the variable Y when Xi has the value xi; and where a, and b1, b2, ... , bk are constants.
Add your answer:
Earn +20 pts
What is Full Regression?
Regression :The average Linear or Non linear relationship between Variables.
Given a linear regression equation of equals 20 - 1.5x where will the point 3 15.5 fall with respect to the regression line?
on the lineGiven a linear regression equation of = 20 - 1.5x, where will the point (3, 15) fall with respect to the regression line?Below the line
Is there any relation between regression and linear equation?
Yes.
Does simple linear regression always go through the origin?
No.
Can dummy variables be used in multiple linear regression analysis?
Yes they can.
What is Full Regression?
Regression :The average Linear or Non linear relationship between Variables.
How is linear regression used?
Linear regression can be used in statistics in order to create a model out a dependable scalar value and an explanatory variable. Linear regression has applications in finance, economics and environmental science.
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.
What is the difference between simple and multiple linear regression?
I want to develop a regression model for predicting YardsAllowed as a function of Takeaways, and I need to explain the statistical signifance of the model.
Given a linear regression equation of equals 20 - 1.5x where will the point 3 15.5 fall with respect to the regression line?
on the lineGiven a linear regression equation of = 20 - 1.5x, where will the point (3, 15) fall with respect to the regression line?Below the line
What has the author ROGER KOENKER written?
ROGER KOENKER has written: 'L-estimation for linear models' -- subject(s): Regression analysis 'L-estimation for linear models' -- subject(s): Regression analysis 'Computing regression quantiles'
Where ridge regression is used?
Ridge regression is used in linear regression to deal with multicollinearity. It reduces the MSE of the model in exchange for introducing some bias.
What is another name for line of best fit?
linear regression
What is the formula of scatter graph method?
I believe it is linear regression.
Is there any relation between regression and linear equation?
Yes.
Does simple linear regression always go through the origin?
No.
Why are your predictions inaccurate using a linear regression model?
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.
