In casting metal parts, molten metal flows through a “gate" into a die that shapes the part. The gate velocity (the speed at which metal is forced through the gate) plays a critical role in die casting. A firm that casts cylindrical aluminum pistons examined 12 types formed from the same alloy. Say that we are interested in how the piston wall thickness (measured in inches) influences the gate velocity (measured in feet per second) chosen by the skilled workers who do the casting. The data is provided below. Thickness Velocity Thickness Velocity 0.248 123.8 0.628 326.2 0.359 223.9 0.697 302.4 0.366 180.9 0.697 145.2 0.400 104.8 0.752 263.1 0.524 228.6 0.806 302.4 0.552 223.8 0.821 302.4 Considering th e coeffcient of determination and regression equation and the scatterplot that this data would generate what can vwe sav

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Question 17
In casting metal parts, molten metal flows through a “gate" into a die that shapes the part. The gate velocity (the speed at which metal is
forced through the gate) plays a critical role in die casting. A firm that casts cylindrical aluminum pistons examined 12 types formed from the
same alloy.
Say that we are interested in how the piston wall thickness (measured in inches) influences the gate velocity (measured in feet per second)
chosen by the skilled workers who do the casting. The data is provided below.
Thickness
Velocity
TII
Velocity
Thickness
0.248
123.8
0.628
326.2
0.359
223.9
0.697
302.4
0.366
180.9
0.697
145.2
0.400
104.8
0.752
263.1
0.524
228,6
0.806
302.4
0.552
223.8
0.821
302.4
Considering the coefficient of determination and regression equation and the scatterplot that this data would generate, what can we say
about the linear relationship that the regression line provides?
O The regression equation is 70.44 + 274.78x and the linear relationship explains about 49.3% of the variation in gate velocity: the large variability in the
scatterplot that the data generates suggests that there may be other factors that should be taken into account.
O The regression equation is 70.31 + 273.21x and the linear relationship explains about 51.2% of the variation in gate velocity: the large variability in the
scatterplot that the data generates suggests that there may be other factors that should be taken into account.
O The regression equation is 60.44 + 271.78x and the linear relationship explains about 59.3% of the variation in gate velocity: the variability in the
scatterplot that the data generates suggests that the linear model is quite adequate, but there may be other factors that should be taken into account.
O The regression equation is 70.22 + 172.37x and the linear relationship explains about 71.2% of the variation in gate velocity: the large variability explained
supports the fit of the linear model extremely well.
Transcribed Image Text:Question 17 In casting metal parts, molten metal flows through a “gate" into a die that shapes the part. The gate velocity (the speed at which metal is forced through the gate) plays a critical role in die casting. A firm that casts cylindrical aluminum pistons examined 12 types formed from the same alloy. Say that we are interested in how the piston wall thickness (measured in inches) influences the gate velocity (measured in feet per second) chosen by the skilled workers who do the casting. The data is provided below. Thickness Velocity TII Velocity Thickness 0.248 123.8 0.628 326.2 0.359 223.9 0.697 302.4 0.366 180.9 0.697 145.2 0.400 104.8 0.752 263.1 0.524 228,6 0.806 302.4 0.552 223.8 0.821 302.4 Considering the coefficient of determination and regression equation and the scatterplot that this data would generate, what can we say about the linear relationship that the regression line provides? O The regression equation is 70.44 + 274.78x and the linear relationship explains about 49.3% of the variation in gate velocity: the large variability in the scatterplot that the data generates suggests that there may be other factors that should be taken into account. O The regression equation is 70.31 + 273.21x and the linear relationship explains about 51.2% of the variation in gate velocity: the large variability in the scatterplot that the data generates suggests that there may be other factors that should be taken into account. O The regression equation is 60.44 + 271.78x and the linear relationship explains about 59.3% of the variation in gate velocity: the variability in the scatterplot that the data generates suggests that the linear model is quite adequate, but there may be other factors that should be taken into account. O The regression equation is 70.22 + 172.37x and the linear relationship explains about 71.2% of the variation in gate velocity: the large variability explained supports the fit of the linear model extremely well.
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