4. An article in the Journal of Environmental Engineering (1989, Vol. 115(3), pp. 608-619) reported the results of a study on the occurrence of sodium and chloride in surface streams in central Rhode Island. The following data are chloride concentration y (in milligrams per liter) and roadway area in the watershed x (in percentage).
4. An article in the Journal of Environmental Engineering (1989, Vol. 115(3), pp. 608-619) reported the results of a study on the occurrence of sodium and chloride in surface streams in central Rhode Island. The following data are chloride concentration y (in milligrams per liter) and roadway area in the watershed x (in percentage).
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
Related questions
Question

Transcribed Image Text:4. An article in the Journal of Environmental Engineering (1989,
Vol. 115(3), pp. 608-619) reported the results of a study on the
occurrence of sodium and chloride in surface streams in central
Rhode Island. The following data are chloride concentration y (in
milligrams per liter) and roadway area in the watershed x (in
percentage).
y
4.4
6.6
9.7
10.6
10.8
10.9
0.19
0.15
0.57
0.70
0.67
0.63
y
11.8
12.1
14.3
14.7
15.0
17.3
0.47
0.70
0.60
0.78
0.81
0.78
y
19.2
23.1
27.4
27.7
31.8
39.5
0.69
1.30
1.05
1.06
1.74
1.62
4.1. Draw a scatter diagram of the data. Does a simple linear
regression model seem appropriate here?
4.2. Fit the simple linear regression model using the method of
least squares.
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