Carbon dioxide is produced by burning fossil fuels such as oil and natural gas, and has been connected to global warming. The following output presents the average amounts (in metric tons) of carbon dioxide emissions for the years 1999-2006 per person in the United States and per person in the rest of the world in an effort to determine if non-US per person emissions can help predict US per person emissions. US 20.2 20 19.8 SUMMARY OUTPUT 19.6 19.4 Regression Statistics Multiple R R Square Adjusted R Square 0.51622776 19.2 0.2664911 19 0.2175905 Standard Error 0.29668345 18.8 Observations 17 18.6 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 ANOVA df MS ignificance F 5.44965 0.0338864 F Regression 0.479683973 0.479684 Residual 15 1.320316027 0.088021 Total 16 1.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 22.8013544 1.416019771 16.10243 7.1E-11 19.78318 25.819529 0.410961292 -2.33445 0.033886 -1.8353112 -0.0834247 Non-US 19.7831797 25.8195291 -0.95936795 -1.8353112 -0.08342469 What is the formula needed to predict US emissions in metric tons if the non-US emissions is 3.4? y = 22.8(3.4) 0.96 y = 22.8 0.96(3.4) ý = 22.8 - 0.96(3.4) Oy = 22.8(3.4)- 0.96

Carbon dioxide is produced by burning fossil fuels such as oil and natural gas, and has been connected to global warming. The following output presents the average amounts (in metric tons) of carbon dioxide emissions for the years 1999-2006 per person in the United States and per person in the rest of the world in an effort to determine if non-US per person emissions can help predict US per person emissions. US 20.2 20 19.8 SUMMARY OUTPUT 19.6 19.4 Regression Statistics Multiple R R Square Adjusted R Square 0.51622776 19.2 0.2664911 19 0.2175905 Standard Error 0.29668345 18.8 Observations 17 18.6 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 3.9 ANOVA df MS ignificance F 5.44965 0.0338864 F Regression 0.479683973 0.479684 Residual 15 1.320316027 0.088021 Total 16 1.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 22.8013544 1.416019771 16.10243 7.1E-11 19.78318 25.819529 0.410961292 -2.33445 0.033886 -1.8353112 -0.0834247 Non-US 19.7831797 25.8195291 -0.95936795 -1.8353112 -0.08342469 What is the formula needed to predict US emissions in metric tons if the non-US emissions is 3.4? y = 22.8(3.4) 0.96 y = 22.8 0.96(3.4) ý = 22.8 - 0.96(3.4) Oy = 22.8(3.4)- 0.96

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Related questions

Q: (1) Do life expectancy and income appear to be associated or independent? (2) Has the relationship…

A: The scatter plot of variable income and life expectancy is given.

Q: 1. Find regression line equation 2. What is the correlation between the interest rate and the yield…

A: Step 1:From above display results a=2.38968653b=0.3961407r2=0.4053168942r=0.63664503y=price of…

Q: The table below shows the January unemployment rate from 2009. 2 3 45 6 78 9 Year 1 Unemployment…

Q: Which of the following is an example of qualitative data that can inform data-driven decision…

A: A data consists of the collection of information in the form of a table which can be used for…

Q: Using the following data, find a linear regression model to calculate Average Salary based on Stress…

Q: Consider the following monthly revenue data for an up-and-coming technology company. Month 1 2 3 4 5…

A: The question is about regression analysis.The data on monthly revenue for up-and-coming technology…

Q: Identify the context for this study. This set of data provided by Blaisdell (1998) can be used to…

A: The following data is given, Temperature Hot Cereal Sales 18 64 10 50 5 80 24 60 38…

Q: The relationship between a company's sales revenues and R&D research is given in the table below.…

A: The question related to the simple linear regression model.The relation between company revenues and…

Q: This small dataset reports the Average Class Size, Combined SAT score, and the pct of the class that…

A: The independent variable is Average Class Size. The dependent variable is Combined SAT Score. We…

Q: t sales 1 324 23 2 245 256 4 567 5 346 16 357 7 357 68 257 9 1678 What is the regression trend…

A: Sales = 33.77 + (90.73*t) Explanation:I will use Excel for run a regression analysis, here are the…

Q: sing the adjusted regression, which house appears to be the best deal according to your regression?…

A: The multiple regression model is Price=a+b1*House Age+b2*Square feet+b3*Bedroom+b4*Brick+b5*Lot…

Q: Develop a formal paper on the following topic. The paper should be verbally and visually…

A: A linear correlation between two variables occurs if the change in one variable affects the change…

Q: Another woman has lean body mass 45 kilograms. What is her predicted metabolic rate? Use the…

A: The regression line Equation is given as: Therefore, the required predicted metabolic rate when…

Q: X/Y Overview - Tutorial Dataset - Redsox project (M1, PCA-X) 0.8- 0.6 04 0.2

A: Graph 1st X/Y overview tutorial dataset of redox project. Greenline indicates R2VX Blueline…

Q: Use this data and develop a model of a truck's annual maintenance expenses based on its weekly usage…

A: Given: n = 10 Formula Used: SSR = b∑XY-∑X∑Yn b = n∑XY-∑X∑Yn∑X2-∑X2

Q: Consider the graph showing the linear relationship between BMI and Fat(%) in a study on metabolic…

A: If the data values shows an upward pattern in a scatter plot, it indicates positive correlation; if…

Q: You think that the amount of scale of industrial growth is directly related to number of species…

Q: Consider the following monthly revenue data for an up-and-coming cyber security company. Month 1 2 3…

A: An up-and-coming cyber security company's monthly revenue data:MonthRevenue(Thousands of…

Q: Data was collected for a regression analysis comparing car weight and fuel consumption. bo was found…

A: Here, the value of y-intercept is 32.7. Interpretation: If x=0, then the intercept is the average…

Q: t

A: Given dataset reports the Average Class Size, Combined SAT score, and the pct of the class that…

Q: What is the population? What is the dependent variable? What is the…

A: The given statement is- A professor at the University of Alabama was interested in evaluating the…

Q: The following correlations were computed as part of a multiple regression analysis that used…

A: Multiple Regression genreal form Y=βo+β1X1+β2X2+...+βnXn+e Where Y=dependent variables X1, X2,…

Q: Sisters and Brothers The scatterplot shows the numbers of brothers and sisters for a large number of…

A: The scatterplot of number of brothers and sisters for a large number of students is given.

Q: Intercept Month Coefficients Standard Error t Stat 460.94771242 29.68313147 15.52894488 28.52012384…

A: Degree of freedom for regression is 1.Degree of freedom for residual is 16.

Q: The personnel director of a large hospital is interested in determining the relationship (if any)…

A: The objective of this question is to find the 95% confidence interval for the average number of sick…

Q: 00 %24 米 Find the slope (to 2 decimal places) of the Least Squares Regression Line from the…

A: We have to find slop..

Q: run a simple regression- dependent variable is Weeks, independent variable is Age. B. run a…

A: A: dependent variable is Weeks Independent variable is Age. Excel Procedure: Enter weeks and Age…

Concept explainers

Equations and Inequations

Equations and inequalities describe the relationship between two mathematical expressions.

Linear Functions

A linear function can just be a constant, or it can be the constant multiplied with the variable like x or y. If the variables are of the form, x2, x1/2 or y2 it is not linear. The exponent over the variables should always be 1.

Question

State the correlation value that best respresents the plot presented.
0.266
0.516
-0.266
O-0.516
Interpret the slope of the line.
For a 1 metric ton increase in US emissions, non-US emissions will, on average, increase by 22.8 metric
tons.
For a 1 metric ton increase in non-US emissions, US emissions will, on average, increase by 22.8 metric
tons.
For a 1 metric ton increase in non-US emissions, US emissions will, on average, decrease by 0.96 metric
tons.
For a 1 metric ton increase in US emissions, non-US emissions will, on average, decrease by 0.96 metric
tons.
We should not interpret the slope in this problem.
Interpret the y
intercept of the line.
On average, when x =
0, non-US emissions are 22.8 metric tons.
On average, when x =
:0, US emissions are –0.96 metric tons.
-
On average, when x =
0, non-US emissions are – 0.96 metric tons.
On average, when x =
0, US emissions are 22.8 metric tons.
%3D
We should not interpret the y - intercept in this problem.
We should interpret the y intercept, but none of the above are correct.

Carbon dioxide is produced by burning fossil fuels such as oil and natural gas, and has been connected to
global warming. The following output presents the average amounts (in metric tons) of carbon dioxide
emissions for the years 1999-2006 per person in the United States and per person in the rest of the world in an
effort to determine if non-US per person emissions can help predict US per person emissions.
US
20.2
20
19.8
SUMMARY OUTPUT
19.6
19.4
Regression Statistics
Multiple R
0.51622776
19.2
R Square
0.2664911
19
Adjusted R Square
0.2175905
Standard Error
0.29668345
18.8
Observations
17
18.6
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
ANOVA
df
MS
ignificance F
Regression
1
0.479683973 0.479684
5.44965 0.0338864
Residual
15
1.320316027 0.088021
Total
16
1.8
Coefficients Standard Error
P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0%
t Stat
Intercept
22.8013544
1.416019771 16.10243
7.1E-11
19.78318 25.819529
0.410961292 -2.33445 0.033886 -1.8353112 -0.0834247
19.7831797
25.8195291
Non-US
-0.95936795
-1.8353112 -0.08342469
What is the formula needed to predict US emissions in metric tons if the non-US emissions is 3.4?
Oy = 22.8(3.4) – 0.96
%3D
|
y = 22.8 - 0.96(3.4)
Oý = 22.8 – 0.96(3.4)
%3D
Oý = 22.8(3.4)- 0.96
%3D

Expert Solution

This question has been solved!

Explore an expertly crafted, step-by-step solution for a thorough understanding of key concepts.

This is a popular solution!

SEE SOLUTION Check out a sample Q&A here

Step 1

VIEW

Step 2

VIEW

Trending now

This is a popular solution!

Step by step

Solved in 2 steps

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

$Linear Equations$

Learn more about

Need a deep-dive on the concept behind this application? Look no further. Learn more about this topic, statistics and related others by exploring similar questions and additional content below.

Similar questions

Part D and E
4.9
hey could any help me with this question please
GRC often rely heavily on raising money for an "annual fund" to support operations. Alumni are typically solicited for donations to the annual fund. Studies suggest that the graduate's annual income is a good predictor of the amount of money he or she would be willing to donate, and there is a reasonably strong, positive, linear relationship between these variables. In the studies described: O a. annual income is the predictor variable O b. the correlation between annual income and the size of the donation is negative. O c. the size of the donation to the annual fund is the predictor variable O d. All of the above O e. None of the above
What percentage of the variation in infant mortality rate is explained by this model? Based on the results of the ANOVA table, is this a good model and why or why not? Is the relationship between percentage of GDP spent on healthcare and infant mortality rate statistically significant? What is the direction of the relationship? For each one percent increase in percentage of GDP spent on health care, we would expect the infant mortality rate to ________ (increase or decrease) by _____.
Carbon dioxide is produced by burning fossil fuels such as oil and natural gas, and has been connected to global warming. The following output presents the average amounts (in metric tons) of carbon dioxide emissions for the years 1999-2006 per person in the United States and per person in the rest of the world in an effort to determine if non-US per person emissions can help predict US per person emissions. US 20.2 20 19.8 SUMMARY OUTPUT 19.6 19.4 Regression Statistics Multiple R 0.51622776 19.2 R Square 0.2664911 19 Adjusted R Square Standard Error 0.2175905 18.8 0.29668345 Observations 17 18.6 3.1 3.2 3.3 3.4 3.5 3.6 3.7 3.8 39 ANOVA df MS F iignificance F Regression 1 0.479683973 0.479684 5.44965 0.0338864 Residual 15 1.320316027 0.088021 Total 16 1.8 Coefficients Standard Error t Stat P-value Lower 95% Upper 95% Lower 95.0% Upper 95.0% Intercept 22.8013544 1.416019771 16.10243 7.16-11 19.78318 25.819529 19.7831797 25.8195291 Non-US -0.95936795 0.410961292 -2.33445 0.033886…
a) Determine the least squares regression equation for the population in years since 2005. Round the slope and y-intercept to the nearest tenth. b) Find the correlation coefficient, r-value, of the line. Round your answer to the nearest thousandth. c) Predict the population for the 2020. ____ thousand people
need help with following
PVan
kln 2.18 The report "Trends in Education 2010: Community Colleges" (www.collegeboard.com/trends) included the accompanying information on student debt for students graduating with an AA degree from a public community college in 2008. Debt Relative Frequency None 0.62 Less than $10,000 0.23 Between $10,000 and $20,000 0.10 More than $20,000 0.05 a. Use the given information to construct a bar chart. b. Comment on student debt for public community college graduates.