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    Regression analysis

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    Need help with this assignment... I am very confused on how to do it. Please show all work and fill out the worksheet below.


    1. Generate a scatterplot. The variables will be weights of cars (x) and the corresponding braking distances (y).

    2. Using the prediction procedure, find the best predicted braking distance for a car that weighs 4000 lbs.
    For #2, first we need to find r the linear correlation coefficient for the data set.
    r for the weight and braking distances = __________
    Next we need to find the critical value, so refer to Table A-6. We have paired data and n = 32.
    Critical value = _________
    Does the linear correlation for the data support a linear correlation?
    The absolute value of r = ___(fill in) is greater than/ is less than (choose one of these statements) the critical value r = __(fill in): There is a linear correlation / there is not a linear correlation (choose one of these decisions) between the weight and braking distance.
    If there is a linear correlation, then we input the necessary data into the prediction equation to find the best predicted value for braking distance for a vehicle weighing 4000 lbs. yhat = b0 + b1x
    If there is not a linear correlation, then we use the sample mean for y as the best predicted braking distance. You'll need to calculate that.
    3. Just for practice, find the regression equation, letting the first variable be the predictor (x) variable. yhat = b0 + b1x

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    Solution Summary

    Step by step method for regression analysis is discussed here. Regression coefficients, coefficient of determination, scatter diagram and significance of regression model are explained in the solution.