Homework Help is Here – Start Your Trial Now!
Math
Advanced Math
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
Advanced Engineering Mathematics
10th Edition
ISBN:9780470458365
Author:Erwin Kreyszig
Publisher:Erwin Kreyszig
Chapter2: Second-order Linear Odes
Section: Chapter Questions
Problem 1RQ
See similar textbooks
icon
Related questions
Question
100%

I need help with part a, thanks

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: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.)
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.)
Expert Solution
steps

Step by step

Solved in 2 steps

SEE SOLUTIONCheck out a sample Q&A here
Blurred answer
Recommended textbooks for you
Advanced Engineering Mathematics
Advanced Engineering Mathematics
Advanced Math
ISBN:
9780470458365
Author:
Erwin Kreyszig
Publisher:
Wiley, John & Sons, Incorporated
Numerical Methods for Engineers
Numerical Methods for Engineers
Advanced Math
ISBN:
9780073397924
Author:
Steven C. Chapra Dr., Raymond P. Canale
Publisher:
McGraw-Hill Education
Introductory Mathematics for Engineering Applicat…
Introductory Mathematics for Engineering Applicat…
Advanced Math
ISBN:
9781118141809
Author:
Nathan Klingbeil
Publisher:
WILEY
Mathematics For Machine Technology
Mathematics For Machine Technology
Advanced Math
ISBN:
9781337798310
Author:
Peterson, John.
Publisher:
Cengage Learning,
Basic Technical Mathematics
Basic Technical Mathematics
Advanced Math
ISBN:
9780134437705
Author:
Washington
Publisher:
PEARSON
Topology
Topology
Advanced Math
ISBN:
9780134689517
Author:
Munkres, James R.
Publisher:
Pearson,
SEE MORE TEXTBOOKS