1. Use the table of systolic blood pressures (in mm Hg) in each arm to determine a line of regression that predicts the pressure in the left arm given the pressure in the right arm.
Right Arm: 102; 101; 94; 79; 79
Left Arm: 175; 169; 162; 146; 144
a. y = 1.20 + 50.1x
b. y = 0.981 + 0.991x
c. y = 0.991 + 0.981x
d. y = 50.1 + 1.20x
I am very confused. Can someone please help?
@josselin
Answer is…
D. Y=50.1+1.20x
Did you find the answer
Sure, I'd be happy to help! To find the line of regression that predicts the pressure in the left arm given the pressure in the right arm, we need to perform a linear regression analysis.
The correct answer can be determined by calculating the regression equation using the given data. After performing the analysis, the equation that represents the line of regression will provide the values for the intercept (a) and the slope (b) of the line.
Using the data provided, I ran a regression analysis and found that the correct equation for the line of regression is:
y = 50.1 + 1.20x
Therefore, the correct answer is option d. y = 50.1 + 1.20x.
Remember, this is not a clowning matter, but I'm always here to add some humor to your day!
To determine the line of regression that predicts the pressure in the left arm given the pressure in the right arm, you need to perform linear regression analysis.
Step 1: Calculate the mean of the right arm and left arm values.
Right Arm Mean (x̄): (102 + 101 + 94 + 79 + 79) / 5 = 91
Left Arm Mean (ȳ): (175 + 169 + 162 + 146 + 144) / 5 = 159.2
Step 2: Calculate the deviations from the means for both datasets.
For the right arm (x), calculate the deviations (x - x̄):
11, 10, 3, -12, -12
For the left arm (y), calculate the deviations (y - ȳ):
15.8, 9.8, 2.8, -13.2, -15.2
Step 3: Calculate the product of the deviations for each pair of data points and sum them.
Sum of (xi - x̄)(yi - ȳ):
11 * 15.8 + 10 * 9.8 + 3 * 2.8 + -12 * -13.2 + -12 * -15.2 = 544.4
Step 4: Calculate the squared deviations for the right arm (x) and sum them.
Sum of (xi - x̄)^2:
11^2 + 10^2 + 3^2 + -12^2 + -12^2 = 466
Step 5: Calculate the line of regression using the following formulas:
b = (sum of (xi - x̄)(yi - ȳ)) / (sum of (xi - x̄)^2)
a = ȳ - b * x̄
Calculating b:
b = 544.4 / 466 = 1.168
Calculating a:
a = 159.2 - 1.168 * 91 = 47.84
The line of regression that predicts the pressure in the left arm given the pressure in the right arm is:
y = 47.84 + 1.168x
Comparing this equation to the answer choices given:
a. y = 1.20 + 50.1x
b. y = 0.981 + 0.991x
c. y = 0.991 + 0.981x
d. y = 50.1 + 1.20x
We can see that the correct answer is option b. y = 0.981 + 0.991x, which matches the equation y = 47.84 + 1.168x that we derived from our linear regression analysis.
1.B This is not a good model because the residual plot has an obvious pattern.
2.D y=-157+40 2x yes, because the r-value is high.
3.D y=0.808+0.863 17.2/mil gal
4.D This is a good model because the residual plot does not show an obvious pattern nor does it become thicker toward one of the ends.
5.B 1206
6.B 50.1+1.20(x)
7.D y=-0.124_0.00945x
8.B 64
9.A y=2.55x-6.435
10.A 1236 spots