Quiz Chapter 06.03: Linear Regression MULTIPLE CHOICE TEST (All Tests) LINEAR REGRESSION (More on Linear Regression) REGRESSION (More on Regression) Pick the most appropriate answer 1. Given \left(x_{1},y_{1} \right), \, \left( x_{2}, y_{2} \right), \, ... \, , \, \left( x_{n}, y_{n} \right) best fitting data to y = f (x) by least squares requires minimization of \, \displaystyle\sum_{i = 1}^{n} \left[ y_{i} - f \left( x_{i} \right) \right] \, \displaystyle\sum_{i = 1}^{n} \left| y_{i} - f \left( x_{i} \right) \right| \, \displaystyle\sum_{i = 1}^{n} \left[ y_{i} - f \left( x_{i} \right) \right]^{2} \, \displaystyle\sum_{i = 1}^{n} \left[ y_{i} - \bar{y} \right]^{2}, \, \bar{y} = \dfrac{ \displaystyle\sum_{i = 1}^{n} y_{i}}{n} 2. The following data x 1 20 30 40 y 1 400 800 1300 is regressed with least square regression to y = a_{0} + a_{1}x. The value of a_{1} is most nearly 27.480 28.956 32.625 40.000 3. The following data x 1 20 30 40 y 1 400 800 1300 is regressed with least square regression to y = a_{1}x. The value of a_{1} is most nearly 27.480 28.956 32.625 40.000 4. An instructor gives the same y vs x data as given below to four students and asks them to regress the data with least squares regression to y = a_{0} + a_{1}x. x 1 10 20 30 40 y 1 100 400 600 1200 Each student comes up with four different answers for the straight-line regression model. Only one is correct. The correct model is y = 60x - 1200 y = 30x - 200 y = -139.43 + 29.684x y = 1 + 22.732x 5. A torsion spring of a mousetrap is twisted through an angle of 180^{\circ}. The torque vs. angle data is given below Torsion, T, N-m 0.110 0.189 0.230 0.250 Angle, \theta, rad 0.10 0.50 1.1 1.5 The amount of strain energy stored in the mousetrap spring in Joules is 0.29872 0.41740 0.84208 1561.8 6. A scientist finds that regressing the y vs x data given below to y = a_{0} + a_{1}x results in the coefficient of determination for the straight-line model, r^{2}, being zero x 1 3 11 17 y 2 6 22 ? The missing value for y at x = 17 most nearly is -2.4444 2.0000 6.8889 34.000 Loading …