**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.

Given that X Y X \cdot YX⋅Y X^2X2 Y^2Y2 4.3 127 546.1 18.49 16129 4.5 121 544.5 20.25…

Answered: A study of the amount of rainfall and…

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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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.) Next
Refer 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.
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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.
For the data in the table, find the regression equation. Here, x gives the number of calories in a hot dog, and y is the number of mg of sodium. Round the slope and y-intercept to two decima below. hen use your equation to answer the question Calories Sodium(mg) 100 311 110 304 120 308 130 337 140 320 160 341 170 375 180 353 190 362 200 372 Every extra 10 calories would be expected to add how many mg of sodium? Submit Question
The 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 Done
please help me answer this for my data analysis class
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.
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The 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.)
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search 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 DELL

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