MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
expand_more
expand_more
format_list_bulleted
Related questions
Question
thumb_up100%
![**Study of Rainfall and Air Pollution**
A research project analyzed the relationship between the amount of rainfall and the quantity of air pollution removed, using the data provided below. The goal is to complete parts (a) and (b) of this study.
### Regression Analysis
(a) **Equation of the Regression Line**
To predict the particulate matter removed based on daily rainfall, determine the equation of the regression line. This equation is represented as \( \hat{y} = \) [calculate and insert coefficients here] \( + \) [calculate and insert coefficients here] \( x \).
Note: The coefficients should be rounded to two decimal places.
### Data Table
**Daily Rainfall and Air Pollution Data**
| Daily Rainfall, \( x \) (0.01 cm) | Particulate Removed, \( y \) (\( \mu g / m^3 \)) |
|-----------------------------------|-------------------------------------------------|
| 4.3 | 127 |
| 4.5 | 121 |
| 5.9 | 117 |
| 5.6 | 119 |
| 6.1 | 114 |
| 5.3 | 119 |
| 3.8 | 133 |
| 2.1 | 142 |
| 7.5 | 107 |
This dataset reflects the varying levels of particulate removal corresponding to different daily rainfall amounts measured in tenths of centimeters.
Note: Use the "Print" option for hard copies of data or calculations as needed.
For further assistance, click "Done" to close the data view or "more help" for additional resources.](https://content.bartleby.com/qna-images/question/e5b1b6e0-7a20-4b1c-9d01-dc71f2c0428f/9806a728-7aad-4109-a205-924cb1787f40/j94kwxa_processed.png)
Transcribed Image Text:**Study of Rainfall and Air Pollution**
A research project analyzed the relationship between the amount of rainfall and the quantity of air pollution removed, using the data provided below. The goal is to complete parts (a) and (b) of this study.
### Regression Analysis
(a) **Equation of the Regression Line**
To predict the particulate matter removed based on daily rainfall, determine the equation of the regression line. This equation is represented as \( \hat{y} = \) [calculate and insert coefficients here] \( + \) [calculate and insert coefficients here] \( x \).
Note: The coefficients should be rounded to two decimal places.
### Data Table
**Daily Rainfall and Air Pollution Data**
| Daily Rainfall, \( x \) (0.01 cm) | Particulate Removed, \( y \) (\( \mu g / m^3 \)) |
|-----------------------------------|-------------------------------------------------|
| 4.3 | 127 |
| 4.5 | 121 |
| 5.9 | 117 |
| 5.6 | 119 |
| 6.1 | 114 |
| 5.3 | 119 |
| 3.8 | 133 |
| 2.1 | 142 |
| 7.5 | 107 |
This dataset reflects the varying levels of particulate removal corresponding to different daily rainfall amounts measured in tenths of centimeters.
Note: Use the "Print" option for hard copies of data or calculations as needed.
For further assistance, click "Done" to close the data view or "more help" for additional resources.
Expert Solution
This question has been solved!
Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.
Step by stepSolved in 2 steps with 1 images
Knowledge Booster
Similar questions
- X₁ is the The volume (in cubic feet) of a black cherry tree can be modeled by the equation y = -51.2 +0.4x₁ + 4.8x2, where tree's height (in feet) and x₂ is the tree's diameter (in inches). Use the multiple regression equation to predict the y-values for the values of the independent variables. (a) x₁ = 73, x₂ = 8.8 (b) x₁ = 67, x₂ = 11.5 (c) x₁ = 85, x₂ = 17.6 (d) x₁ = 92, x₂ = 20.8 cubic feet. (a) The predicted volume is (Round to one decimal place as needed.) (b) The predicted volume is cubic feet. (Round to one decimal place as needed.) (c) The predicted volume is cubic feet. (Round to one decimal place as needed.) (d) The predicted volume is cubic feet. (Round to one decimal place as needed.) Nextarrow_forwardRefer to the data set: x -1 1 -2 3 0 2 y 9 2 15 1 4 1.5 Part a: Make a scatterplot and determine which type of model best fits the data.Part b: Find the regression equation, round decimals to one place.Part c: Use the equation from Part b to determine y when x = 5.arrow_forwardPlease give solution in correct and step by step detailed format thankuarrow_forward
- Name: Shalisha Robertson Topic 30-8th Core Hours spent looking for Shooting Stars Number of shooting stars seen 0 2 0 3 2 4 1 4 2 6 4 6 2 7 What is the equation of your regression line for this data eate a scatter plot with your regression line drawn in.arrow_forwardThe data provided give the number of standby hours based on total staff present, X₁, and remote hours, X₂. Perform a multiple regression analysis using the data provided and determine the VIF for each independent variable in the model. Is there reason to suspect the existence of collinearity? Click the icon to view the data. Determine the VIF for each independent variable in the model. | VIF ₂2 = VIF₁ = (Round to three decimal places as needed.) Is there reason to suspect the existence of collinearity? OA. No. The VIF for each independent variable is less than 5. B. Yes. The VIF for each independent variable is greater than 5. OC. No. The VIF for each independent variable is greater than 5. OD. Yes. The VIF for each independent variable is less than 5. wwwwwww Table of Data Standby Total Staff Hours Present 245 330 274 358 195 197 117 153 115 275 200 236 336 339 321 303 286 329 352 323 Remote Hours 417 655 524 385 349 350 388 153 278 479 Print Donearrow_forwardplease help me answer this for my data analysis classarrow_forward
- Part a: Make a scatter plot and determine which type of model best fits the data.Part b: Find the regression equation.Part c: Use the equation from Part b to determine y when x = 1.5.arrow_forwardUse the given data set to answer parts (a) and (b). a. Find the regression equation for the data points. X 5 b. Graph the regression equation and the data points. y -1 10 -10 y B. 10 -10- C. a. Find the regression equation for the data points. ŷ-0 (Use integers or decimals for any numbers in the expression. Round to two decimal places as needed.) b. Graph the regression equation and the data points. O A. 10 T -10- 1 2 -1 3 327 D. -10 4 y 4 28 0arrow_forwardThe table shows the amounts of crude oil (in thousands of barrels per day) produced by a certain country and the amounts of crude oil (in thousands of barrels per day) imported by the same country for seven years. The equation of the regression line is y = - 1.269x + 16,635.60. Complete parts (a) and (b) below. Produced, x Imported, y 5,718 5,612 5,409 5,228 5,128 5,006 O 9,106 9,631 10,000 10,140 10,133 10,059 5,759 9,318 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.)arrow_forward
- Using the weights (Ib) and highway fuel consumption amounts (mi/gal) of the 48 cars listed in the accompanying data set, one gets this regression equation: y = 58 9-0.00749x, where x represents weight Complete parts (a) through (d). Click the icon to view the car data. 東 b. What are the specific values of the slope and y-intercept of the regression line? O A. The slope is 58.9 and the y-intercept is 0.007499. B. The slope is -0.00749 and the y-intercept is 58.9. O C. The slope is 58.9 and the y-intercept is -0.00749. O D. The slope is 0.00749 and the y-intercept is 58.9. c. What is the predictor variable? O A. The predictor variable is highway fuel consumption, which is represented by x. B. The predictor variable is weight, which is represented by x. O C. The predictor variable is weight, which is represented by y O D. The predictor variable is highway fuel consumption, which is represented by y. d. Assuming that there is a significant linear correlation between weight and highway fuel…arrow_forwardsearch Refer to the data set: y X -3 -2 =1 -00 .......... 1 8 1 7 −IN 01 1 2 2 4 Part a: Make a scatter plot and determine which type of model best fits the data. Part b: Find the regression equation. Part c: Use the equation from Part b to determine y when x = 5 For the toolbar, press ALT+F10 (PC) or ALT+FN+F10 (Mac). BIUS Paragraph V Arial h V © O Click Save and Submit to save and submit. Click Save All Answers to save all answers. 10pt DELLarrow_forwardAn oceanographer measured the length, in meters, of a deepwater wave and its speed, in meters per second. The results are shown in the following table. (a) Find the equation of a linear regression line for the data where wave length is the independent variable, x, and speed is the dependent variable. (Round your numerical values to two decimal places.) y= ? (b) Using the equation from part (a), estimate the speed (in meters per second) of a wave that is 200 m long. (Round your answer to one decimal place.) ? m/sarrow_forward
arrow_back_ios
arrow_forward_ios
Recommended textbooks for you
- MATLAB: An Introduction with ApplicationsStatisticsISBN:9781119256830Author:Amos GilatPublisher:John Wiley & Sons Inc
Probability and Statistics for Engineering and th...StatisticsISBN:9781305251809Author:Jay L. DevorePublisher:Cengage Learning
Statistics for The Behavioral Sciences (MindTap C...StatisticsISBN:9781305504912Author:Frederick J Gravetter, Larry B. WallnauPublisher:Cengage Learning 
Elementary Statistics: Picturing the World (7th E...StatisticsISBN:9780134683416Author:Ron Larson, Betsy FarberPublisher:PEARSON
The Basic Practice of StatisticsStatisticsISBN:9781319042578Author:David S. Moore, William I. Notz, Michael A. FlignerPublisher:W. H. Freeman
Introduction to the Practice of StatisticsStatisticsISBN:9781319013387Author:David S. Moore, George P. McCabe, Bruce A. CraigPublisher:W. H. Freeman
MATLAB: An Introduction with Applications
Statistics
ISBN:9781119256830
Author:Amos Gilat
Publisher:John Wiley & Sons Inc
Probability and Statistics for Engineering and th...
Statistics
ISBN:9781305251809
Author:Jay L. Devore
Publisher:Cengage Learning
Statistics for The Behavioral Sciences (MindTap C...
Statistics
ISBN:9781305504912
Author:Frederick J Gravetter, Larry B. Wallnau
Publisher:Cengage Learning
Elementary Statistics: Picturing the World (7th E...
Statistics
ISBN:9780134683416
Author:Ron Larson, Betsy Farber
Publisher:PEARSON
The Basic Practice of Statistics
Statistics
ISBN:9781319042578
Author:David S. Moore, William I. Notz, Michael A. Fligner
Publisher:W. H. Freeman
Introduction to the Practice of Statistics
Statistics
ISBN:9781319013387
Author:David S. Moore, George P. McCabe, Bruce A. Craig
Publisher:W. H. Freeman