Concentrations of a pollutant were measured at 25 locations in a lake after rains caused heavy runoff from surrounding areas. After a period of dry weather, they were measured again at the same locations. The data is attached in the image below. (a) Perform an appropriate hypothesis testing to see if there is any effect of the runoff on pollutant concentrations. (b) Find a 90% confidence interval for the effect of runoff on pollutant concentrations.
Concentrations of a pollutant were measured at 25 locations in a lake after rains caused heavy runoff from surrounding areas. After a period of dry weather, they were measured again at the same locations. The data is attached in the image below. (a) Perform an appropriate hypothesis testing to see if there is any effect of the runoff on pollutant concentrations. (b) Find a 90% confidence interval for the effect of runoff on pollutant concentrations.
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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Solve manually and also please mention the r-studio code, not the excel output formulas. Thanks so much!
Concentrations of a pollutant were measured at 25 locations in a lake after rains caused heavy runoff
from surrounding areas. After a period of dry weather, they were measured again at the same
locations. The data is attached in the image below.
(a) Perform an appropriate hypothesis testing to see if there is any effect of the runoff on pollutant
concentrations.
(b) Find a 90% confidence interval for the effect of runoff on pollutant concentrations.
Transcribed Image Text:**Weather Probability Data**
This table presents data on the probability of two weather conditions: "rainy" and "dry." Each pair of numbers represents the likelihood of these weather conditions occurring.
| Rainy Probability | Dry Probability |
|-------------------|-----------------|
| 0.1622 | 0.1515 |
| 0.1352 | 0.1237 |
| 0.0939 | 0.0735 |
| 0.1968 | 0.1151 |
| 0.1495 | 0.1158 |
| 0.1496 | 0.1125 |
| 0.1898 | 0.1192 |
| 0.1338 | 0.1311 |
| 0.1737 | 0.0975 |
| 0.1333 | 0.0879 |
| 0.0672 | 0.0714 |
| 0.1777 | 0.1216 |
| 0.1216 | 0.1334 |
| 0.2709 | 0.1186 |
| 0.1914 | 0.1362 |
| 0.0973 | 0.0263 |
| 0.1981 | 0.0687 |
| 0.1226 | 0.1309 |
| 0.1492 | 0.1495 |
| 0.0342 | 0.0535 |
| 0.1511 | 0.0788 |
| 0.1503 | 0.1312 |
| 0.1062 | 0.1177 |
| 0.2072 | 0.1557 |
| 0.1258 | 0.0883 |
This data can be useful for understanding seasonal weather patterns and making predictions based on historical probabilities.
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