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 MULTIPLE CHOICE TEST LINEAR REGRESSION REGRESSION

Q1.  Given (x1,y1), (x2,y2), ..., (xn,yn) best fitting data to y=f(x) by least squares requires minimization of

Q2. The following data

 1 20 30 40 1 400 800 1300

is regressed with least squares regression to y=a0+a1x.  The value of a1 most nearly is

27.480

28.956

32.625

40.000

Q3. The following data

 1 20 30 40 1 400 800 1300

is regressed with least squares regression to y=a1x.  The value of y=a1x most nearly is

27.480

28.956

32.625

40.000

Q4.  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=a0+a1x.

 1 10 20 30 40 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+22.782x

Q5A torsion spring of a mousetrap is twisted through an angle of 1800.  The torque vs angle data is given below.

 Torsion, T, N-m 0.11 0.189 0.23 0.25 Angle, θ, rad 0.1 0.5 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

Q6.  A scientist finds that regressing the y vs x data given below to y=a0+a1x results in the coefficient of determination for the straight-line model,r2 being zero.

 x 1 3 11 17 2 6 22 ?

The missing value for y at x=17 most nearly is

-2.4444

2.0000

6.8889

34.000

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