Fish Biomass Data y x1 x2 X3 x4 100 14.3 15.0 12.2 48.0 388 19.1 29.4 26.0 152.2 755 54.6 58.0 24.2 469.7 1288 28.8 42.6 26.1 485.9 230 16.1 15.9 31.6 87.6 0 10.0 56.4 23.3 6.9 551 28.5 95.1 13.0 192.9 345 13.8 60.6 7.5 105.8 0 10.7 35.2 40.3 0.0 348 25.9 52.0 40.3 116.6 An experiment was conducted to study the effect of stream characteristics on fish biomass. The regressor variables are as follows: average depth (of 50 cells), x₁; area of in-stream cover (i.e., undercut banks, logs, boulders, etc.), X2; percent canopy cover (average of 12), x3; and area ≥25 centimeters in depth, x4. The response is y, the fish biomass. Use the accompanying data to complete parts (a) through (c). Click the icon to view the fish biomass data. (a) Fit a multiple linear regression including all four regression variables. ŷ = + (1) ×₁ + (×2 + (×3+ (×4 (Round the constant and x₁-coefficient to the nearest integer as needed. Round all other coefficients to two decimal places as needed.)
Fish Biomass Data y x1 x2 X3 x4 100 14.3 15.0 12.2 48.0 388 19.1 29.4 26.0 152.2 755 54.6 58.0 24.2 469.7 1288 28.8 42.6 26.1 485.9 230 16.1 15.9 31.6 87.6 0 10.0 56.4 23.3 6.9 551 28.5 95.1 13.0 192.9 345 13.8 60.6 7.5 105.8 0 10.7 35.2 40.3 0.0 348 25.9 52.0 40.3 116.6 An experiment was conducted to study the effect of stream characteristics on fish biomass. The regressor variables are as follows: average depth (of 50 cells), x₁; area of in-stream cover (i.e., undercut banks, logs, boulders, etc.), X2; percent canopy cover (average of 12), x3; and area ≥25 centimeters in depth, x4. The response is y, the fish biomass. Use the accompanying data to complete parts (a) through (c). Click the icon to view the fish biomass data. (a) Fit a multiple linear regression including all four regression variables. ŷ = + (1) ×₁ + (×2 + (×3+ (×4 (Round the constant and x₁-coefficient to the nearest integer as needed. Round all other coefficients to two decimal places as needed.)
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
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Question
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I need help with part a, thanks
Transcribed Image Text:Fish Biomass Data
y
x1
x2
X3
x4
100
14.3
15.0
12.2
48.0
388
19.1
29.4
26.0
152.2
755
54.6
58.0
24.2
469.7
1288
28.8
42.6
26.1
485.9
230
16.1
15.9
31.6
87.6
0
10.0
56.4
23.3
6.9
551
28.5
95.1
13.0
192.9
345
13.8
60.6
7.5
105.8
0
10.7
35.2
40.3
0.0
348
25.9
52.0
40.3
116.6
Transcribed Image Text:An experiment was conducted to study the effect of stream characteristics on fish biomass. The regressor variables
are as follows: average depth (of 50 cells), x₁; area of in-stream cover (i.e., undercut banks, logs, boulders, etc.), X2;
percent canopy cover (average of 12), x3; and area ≥25 centimeters in depth, x4. The response is y, the fish biomass.
Use the accompanying data to complete parts (a) through (c).
Click the icon to view the fish biomass data.
(a) Fit a multiple linear regression including all four regression variables.
ŷ = + (1) ×₁ + (×2 + (×3+ (×4
(Round the constant and x₁-coefficient to the nearest integer as needed. Round all other coefficients to two decimal
places as needed.)
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