Prediction of Risk for strock from regression model.

A 10 year study by the American Heart Association provided data on how age, blood pressure and smoking relate to the risk of strokes. Data from a portion of this study are shown below. Risk is interpreted as the probability (times 100) that a person will have a stroke over the next 10 year period. For the smoker variable, 1 indicates that the person is a smoker and 0 indicates a non-smoker.

A) If you could choose only 1 of the variables to help you predict the Risk, which variable would you choose? Why? How good would that model be, in terms of predicting the Risk?
B) Are there any of the independent variables that should not be in the model at the same time when you are trying to predict the Risk? If so, which variables? Why?
C) Develop the "best" regression model possible using this set of variables to help you predict the Risk. State your final model. Interpret the coefficients for the model (i.e. what do the numbers mean?). Finally, tell me how to use this model for predicting a person's risk of a stroke. Illustrate this with numbers and interpret its meaning.

1)Given the regression equation: Y = 1.3479 + 0.3978 X, what is the fitted value (orY ? ) if X = -3?
2) Calculate bo, b1 for the information provide below
X Y
-2 9
0 5
-0.5 7
1 100

12.33 Use Excel's Add Trend-line feature to fit a linear regression to the scatter plot. Is a linear model credible?
12.35 Use Megastat to fit the regression model, including residuals and standardized residuals.
12.37 ( a) based on the R2 and ANOVA table for your model, how would you assess the fit? (b) Interpret the p-v

Ho: Total home cost increases with additional square feet
Ha: Total home cost does not increase with additional square feet
Define bivariate regression, discuss fitted regression and using regressionforprediction purposes.
Please see attached data and help me to understand what each section means.

The following data has been collected for two variables, X and Y.
X Y
5 30
10 41
15 53
20 62
25 67
A simple linear regression model has been constructed using the data in the table and is being used to predict values for the variably Y
Of 3, 7, 18 and 35, how do I determine which for variable X would lead to

Given the Excel output below of x = entrance scores achieved by students and y = GPA
SUMMARY OUTPUT
Regression Statistics
Multiple R 0.883582
R Square 0.780718
Adjusted R

In the real world, whenever, we publish a regression model for use in prediction we take special care to make sure any reader or potential user of the model knows the lowest and highest values from each data set involved in development of the regressionmodel. What are these values important? Describe a specific problem that c

Please solve the exercise below:
Consider the following partial computer output for a multiple regressionmodel.
Predictor Coefficient Standard Deviation
Constant 41.225 6.380
X1 1.081 1.353
X2 -18.404