Question

In: Statistics and Probability

Possum - Regression X: headL (mm) Y: totalL (cm) Y-Hat Residual 94.1 89 92.5 91.5 94...

Possum - Regression

X: headL (mm) Y: totalL (cm) Y-Hat Residual
94.1 89
92.5 91.5
94 95.5
93.2 92
91.5 85.5
93.1 90.5
95.3 89.5
94.8 91
93.4 91.5
91.8 89.5
93.3 89.5
94.9 92
95.1 89.5
95.4 91.5
92.9 85.5
91.6 86
94.7 89.5
93.5 90
94.4 90.5
94.8 89
95.9 96.5
96.3 91
92.5 89
94.4 84
95.8 91.5
96 90
90.5 85
93.8 87
92.8 88
92.1 84
92.8 93
94.3 94
91.4 89
90.6 85.5
94.4 85
93.3 88
89.3 82.5
92.4 80.5
84.7 75
91 84.5
88.4 83
85.3 77
90 81
85.1 76
90.7 81
91.4 84
90.1 89
98.6 85
95.4 85
91.6 88
95.6 85
97.6 93.5
93.1 91
96.9 91.5
103.1 92.5
99.9 93.7
95.1 93
94.5 91
102.5 96
91.3 88
95.7 86
91.3 90.5
92 88.5
96.9 89.5
93.5 88.5
90.4 86
93.3 85
94.1 88.5
98 88
91.9 87
92.8 90
85.9 80.5
82.5 82
88.7 83
93.8 89
92.4 89
93.6 84
86.5 81
85.8 81
86.7 84
90.6 85.5
86 82
90 81.5
88.4 80.5
89.5 92
88.2 86.5
98.5 93
89.6 87.5
97.7 84.5
92.6 85
97.8 89
90.7 85
89.2 82
91.8 84
91.6 88.5
94.8 83
91 86
93.2 84
93.3 86.5
89.5 81.5
88.6 82.5
92.4 89
91.5 82.5
93.6 89

Solutions

Expert Solution


Related Solutions

Possums: Head-Length (mm) Body-Length (cm) Y-hat Residuals 94.1 89 92.5 91.5 94 95.5 93.2 92 91.5...
Possums: Head-Length (mm) Body-Length (cm) Y-hat Residuals 94.1 89 92.5 91.5 94 95.5 93.2 92 91.5 85.5 93.1 90.5 95.3 89.5 94.8 91 93.4 91.5 91.8 89.5 93.3 89.5 94.9 92 95.1 89.5 95.4 91.5 92.9 85.5 91.6 86 94.7 89.5 93.5 90 94.4 90.5 94.8 89 95.9 96.5 96.3 91 92.5 89 94.4 84 95.8 91.5 96 90 90.5 85 93.8 87 92.8 88 92.1 84 92.8 93 94.3 94 91.4 89 90.6 85.5 94.4 85 93.3 88 89.3...
a. Develop an estimated regression equation for the data of the form y-hat = bo + b1 x.
Consider the following data for two variables, X and Y X 6 29 21 15 24 Y 10 30 22 14 25 a. Develop an estimated regression equation for the data of the form y-hat = bo + b1 x. Comment on the adequacy of this equation for predicting y . Enter negative value as negative number. The regression equation is Y = [          ] + [            ] X (to 2 decimals)   S = [       ] (to 3 decimals)...
A wire with a radius R = .89 mm and length 45 cm is made of...
A wire with a radius R = .89 mm and length 45 cm is made of two materials, Carbon and Nichrome (resistivity not given I assume it needs to be googled). The Carbon portion is 15 cm long. The temperature of the wire is 75 oC. The wire is connected to a 12 volt battery. a) Find the total Resistance of the battery as well as the current (I) and the current density (J) and the electric field (E) in...
1- The regression of X on Y is not the same as the regression of Y...
1- The regression of X on Y is not the same as the regression of Y on X. Why is this? Select one: a. Because the regression minimises the residuals of y, not the residuals of x. b. Because unlike correlation, regression assumes X causes Y. c. Because one goes through (mean x, mean y) whereas the other goes through (mean y, mean x). d. Because the F test divides MSy by MSx, not the other way round. 2- Using...
Regression Analysis. Calculate when y hat = 9,500 – 250(x) when age = 10, 15, 20,...
Regression Analysis. Calculate when y hat = 9,500 – 250(x) when age = 10, 15, 20, and 22 with an asking price of $8,000 6,000, 5,000 and 4,200 respectively. 1. Sum of Squared Errors (SSE) 2. Total Sum of Squares (TSS) 3. Sum of Squares of Regression (SSR) 4. The calculated value that represents the explained variation. 5. What is the calculated value that represents the unexplained variation 6. What is the value of the coefficient of determination.
Given student data: USING R y=c(81.72, 91.5, 90, 75.21, 68.11, 95.27, 95, 89.71, 92.5) x1=c(60, 62,...
Given student data: USING R y=c(81.72, 91.5, 90, 75.21, 68.11, 95.27, 95, 89.71, 92.5) x1=c(60, 62, 68, 59, 61, 70, 70, 65, 66) x=c('B', 'A', 'B', 'A', 'A', 'B', 'B', 'B', 'A') Y represents the grade scores per semester , x1 represents the student’s height in inches, and x2 represents the major( A = architecture, B = business) Question 1 1. Build a linear regression model relating grade scores y to student height x1 and the type of major x2....
Given student data: USING R please y=c(81.72, 91.5, 90, 75.21, 68.11, 95.27, 95, 89.71, 92.5) x1=c(60,...
Given student data: USING R please y=c(81.72, 91.5, 90, 75.21, 68.11, 95.27, 95, 89.71, 92.5) x1=c(60, 62, 68, 59, 61, 70, 70, 65, 66) x=c('B', 'A', 'B', 'A', 'A', 'B', 'B', 'B', 'A') Y represents the grade scores per semester , x1 represents the student’s height in inches, and x2 represents the major( A = architecture, B = business) Question 1 1. Build a linear regression model relating grade scores y to student height x1 and the type of major...
Running a linear regression produces the following : hat y =37.5-12.75x r = - 0.72 r...
Running a linear regression produces the following : hat y =37.5-12.75x r = - 0.72 r ^ 2 = 0.52 SE slope =2.85 n = 29 a) Is this a positive or negative correlation? How do you know? b) Without running the t-tests, does this appear to be a strong correlation? c) Based on the test statistic t = (slope)/(SESlope) can we claim there is correlation?
A particular conductor is x = 50.0 mm long by y = 10.0 mm wide by...
A particular conductor is x = 50.0 mm long by y = 10.0 mm wide by z = 1.0 mm thick. This conductor is inserted into a 0.50 T magnetic field aligned parallel to the z-axis. When a 1.00 A current passes through the strip parallel to the x-axis, the Hall voltage is 100.0 µV. What is the density of charge carriers in the conductor? (1) 8.9 x 1024 m-3 (2) 3.1 x 1025 m-3 (3) 5.4 x 1025 m-3...
Write a program for Sense HAT (or the emulator) to map X, Y, and Z acceleration...
Write a program for Sense HAT (or the emulator) to map X, Y, and Z acceleration (or orientation) values into R, G, and B color values on the LED matrix. That way, when you tilt the Sense HAT, the LED matrix will display different colors to simulate a paint mixer. When you write your program, please consider using delay to avoid the problem of changing color too fast to be perceived. Also, you want to make sure that you map...
ADVERTISEMENT
ADVERTISEMENT
ADVERTISEMENT