Option(C): 70%
>> Coefficient of determination,
r2 = SS(Regression)/SS(Total) = 374.285/537.728 = 0.69604 ≈ 0.70
Approximately 70% of the sample variation in acceleration time can be explained by the simple linear model.
In a comprehensive road test on new car models, one variable measured is the time it...
PART I. Multiple Choice. Cirele the letter to the correct answer on the front page 1. Below is a list of assumptions necessary for the regression analysis to be valid. With each assumption is a proposed procedure (on the right) for checking the validity of the assumption. Select the assumption validity which is the correct match. a. Normal errors b. Constant error variance C. Plot of residuals versus x Plot of residuals versus x Histogram of residuals Look for outliers...
PART I. Multiple Choice. Cirele the letter to the correct answer on the front page 1. Below is a list of assumptions necessary for the regression analysis to be valid. With each assumption is a proposed procedure (on the right) for checking the validity of the assumption. Select the assumption validity which is the correct match. a. Normal errors b. Constant error variance C. Plot of residuals versus x Plot of residuals versus x Histogram of residuals Look for outliers...
3. [25 marks] Some female psychology students were investigating whether intelligence depends on brain size. They each took a standard test that measured verbal IQ and also underwent an MRI scan to measure their brain size. The resulting data is below, file named IQBrain.csv. IQ BrainV 132 816.932 132 951.545 90 928.799 136 991.305 90 854.258 129 833.868 120 856.472 100 878.897 71 865.363 132 852.244 112 808.02 129 790.619 86 831.772 90 798.612 83 793.549 126 866.662 126 857.782...
1. For each of the following regression models, write down the X matrix and 3 vector. Assume in both cases that there are four observations (a) Y BoB1X1 + B2X1X2 (b) log Y Bo B1XiB2X2+ 2. For each of the following regression models, write down the X matrix and vector. Assume in both cases that there are five observations. (a) YB1XB2X2+BXE (b) VYBoB, X,a +2 log10 X2+E regression model never reduces R2, why 3. If adding predictor variables to a...