regression

  1. M

    Regression [R2] Model Attributes Question

    A regression was performed to predict selling price of houses based on Price in dollars, Area in square feet, Lotsize in square feet, and Age in years. The R2 is 92%. The equation from this regression is given here Price = 169328 + 35.3 Area + 0.718 Lotsize – 6543 Age Which of the following...
  2. M

    Regression Questions Need Help

    6. _______A regression was performed to predict selling price of houses based on Price in dollars, Area in square feet, Lotsize in square feet, and Age in years. The R2 is 92%. The equation from this regression is given here Price = 169328 + 35.3 Area + 0.718 Lotsize – 6543 Age Which of the...
  3. W

    Regression Questions

    Hi Guys, I have some theoretical questions about regression models, I need an answer of true or false for the next few phrases.... 1. Leverage values increase when the sample variance increase 2. in a simple model, the residuals ei is dependent with the predicted values of yi 3. when the...
  4. R

    Testing if a coefficient is a multiple of another coefficient in a regression

    Hi, my question on a worksheet is 'How would you test that the coefficient on age is 100 times the coefficient on wage?' (both age and wage are thus regressors with the dependent variable being marital status). I have a stata output which gives coefficients and standard errors for the...
  5. D

    Question about F-Test for comparing multiple regression models

    So the equation for comparing two multiple regression models using an F-test is When we're calculating this to compare our models, do we use the Sum of Sqaures for the model, or the Sum or Squares for the Error?
  6. J

    Calculating Datapoints Regression - Help ?

    Data collected from the state of Florida includes: y = crime rate = Annual number of crimes in county per 1000 population x1 = education = Percentage of adults in county with at least a high school education x2 = urbanization = Percentage in county living in an urban environment...
  7. L

    Linear Regression: parameter estimation of alpha and beta?

    Could anyone help me with the part of this question highlighted in the link? I can derive the first part, but i'm having problems canceling alpha, any help would be greatly appreciated!
  8. F

    Correlation & linear regression

    Y and Z are two random variables with Correlation of YZ of 0.5 IF X=2Z-1, then correlation of XZ is equal to; Can anyone help? Thanks in advance (Happy)
  9. S

    multiple regression, binary

    Hi there, im currently attempting to do multiple regression for an assignment. I have a binary variable for one of my categories, which is for male or female. Is there any considerations i must take about adjusting this or modifying before applying to the model? many thanks
  10. M

    Is an un-bootstrapped model ever better than a bootstrapped one?

    Hi, I have made a transfer function (WA-PLS model) that infers water-table depths of peat bogs based on water-table depths that have already been measured and the testate amoebae species found at these w-t depths. Now to the statistics part of this; I have a two models, an un-bootstrapped...
  11. M

    Changes in the Regression Coefficient

    Under what condition (or conditions if you think it necessary) would one observe no change in the regression coefficient (e.g., b-hat y on X1) for some variable when another variable is added to the regression equation?
  12. J

    Regression in Statistics Question

    For a multiple regression model, SST = 189, and SSE = 30, then the proportion of the total variation in the observed y’s that is not explained by the model is? Please show work + answer. I've tried different formulas such as sst - sse and found a site saying ss/sst Can someone please...
  13. S

    Residuals from a regression

    Define the residual from a regression (one independent variable) algebraically and show that: a. the mean of the residuals is zero b. the correlation of the residuals and the independent variable is zero. Any help would be greatly appreciated, thanks!
  14. S

    Regression Analsys Model

    Hello I wanted to create a regression model based on the following data: United States Crime Rates 1960 - 2009 For my model, I wanted to estimate the population of US based on reported crime (murder, theft, etc...), and I wanted to know if it's a good idea for a model because you can clearly...
  15. S

    Categorical and binary responses in multiple linear regression

    Hi there Im trying to apply some data to a multiple regression model. The issue i am having is that some of the variables are binary responses, and some are categorical, can any one please help me with how to get it into a form where i can apply straight into a multiple linear regression model...
  16. D

    Finding a regression equation from mean, std-dev and correlation

    There are two variables, X1 and X2, sample size N=1000. X1 has a mean of 72 with stddev = 12 and X2 has a mean of 62 with a stddev=18. The correlation coefficient between the two variables is 0.600. How can this information be used to find a regression equation X2 = B0 + B1(X1) with slope B1...
  17. K

    Which regression should I use for this data?

    Hello there, I have done a few observations: x | y --------+------- 150 | 7.4 130 | 11.6 110 | 18.8 90 | 33.2 70 | 61.4 50 | 120.8 30 | 239.8 20 | 335.0 10 | 453.0 5 | 518.8 0 | 587.4 -5 | 655.2 -10 | 721.0 -20 |...
  18. S

    Constructing a confidence interval for a regression coefficient

    Hi all, this is my first time posting here but I've been reading through the forums and it's been a great help so far. So thanks to everyone for their great help in the past :) My question is this. I've been given the following regression: weight = -99.41 + 3.94(height); R(squared) = 0.81...
  19. S

    Multiple regression coefficents

    Hi there, im currently working on a research project that requires making usage of multiple regression. I am really struggling to find any proofs or methods of derivation for the coefficients used in the linear regression line. I know for normal simple regression we use least means squared...
  20. S

    Curve fitting when typical regression models fail

    I tried using a regression model to fit a curve, but none of the typical models work. I'm not smart enough to use other regression methods, but I'm thinking an equation can be derived without it (hopefully). The scatter plot shows Average Weight on the y-axis, and a ratio of the quantities...