The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thodsands of barrels per day imported by a country, for the last seven years. Construct and interpret a 90% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,464 thousand barrels per day. The equation of the regression line is y = - 1.166x + 16,080.356. Oil produced, x Oil imported, y 5,849 5,734 5,603 5.406 5,152 5,076 5,050 9,328 9.114 9,600 10,072 10,190 10,119 10,002 Construct and interpret a 90% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,464 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. There is a 90% chance that the predicted amount of oil imported is between and thousand barrels, when there are 5,464 thousand barrels produced. O B. We can be 90% confident that when the amount of oil produced is 5.464 thousand barrels, the amount of oil imported will be between and

The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thodsands of barrels per day imported by a country, for the last seven years. Construct and interpret a 90% prediction interval for the amount of crude oil imported by the this country when the amount of crude oil produced by the country is 5,464 thousand barrels per day. The equation of the regression line is y = - 1.166x + 16,080.356. Oil produced, x Oil imported, y 5,849 5,734 5,603 5.406 5,152 5,076 5,050 9,328 9.114 9,600 10,072 10,190 10,119 10,002 Construct and interpret a 90% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,464 thousand barrels per day. Select the correct choice below and fill in the answer boxes to complete your choice. (Round to the nearest cent as needed.) O A. There is a 90% chance that the predicted amount of oil imported is between and thousand barrels, when there are 5,464 thousand barrels produced. O B. We can be 90% confident that when the amount of oil produced is 5.464 thousand barrels, the amount of oil imported will be between 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

See similar textbooks

Related questions

Q: first year college students were selected with their grades in Grade 12 Math and Math in the Modern…

A: Here we are given x…

Q: Question 4: Trying to determine the number of students to accept is a tricky task for universities.…

Q: The following data give the percentage of women working in five companies in the retail and trade…

A: Given data, X Y X*Y X*X 68 50 3400 4624 45 21 945 2025 73 65 4745 5329 55 47 2585 3025…

Q: The table shows the total square footage (in billions) of retailing space at shopping centers and…

A: The data indicates the total square footage of retailing space at shopping centers and their sales…

Q: If a regression line were defined by the linear equation Y = 2x + 6, what is a participant's…

A: Given regression linear equation is Y=2x+6 If X=3 y=?

Q: The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a…

A: Given data of export and import of crude oil as shown below The given regression line equation is…

Q: The table below shows the average weekly wages (in dollars) for state government employees and…

A: Given information: The regression equation line is: y^=1.481x-63.795 The data is provided as: x…

Q: Smokers don’t live as long (on average) as nonsmokers, and heavy smokers don’t live as long as light…

A: More smoking less survival time.

Q: We want to predict the percentage weight loss for 2011 participants, based on 2010 data. If we…

A: Step 1:We want to predict the simple linear regression model where starting weight(xi) is a…

Q: The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A…

A: The question is about regression.Given :Regression equation :To find :Value of coefficient of…

Q: The following table shows the mass of an object recorded over time. Time (min) Mass (g) 19 30 24…

Q: The table shows the number of goals allowed and the total points earned (2 points for a win, and 1…

A: (a) The regression analysis is conducted using EXCEL. The software procedure is given below: Enter…

Q: The equation used to predict college GPA (range 0-4.0) is y=0.18+0.53x1+0.002x2, where x1 is high…

A: Given, The equation used to predict college GPA is y=0.18+0.53x1+0.002x2, where x1 is high school…

Q: 1. The scatterplot shows the relationship between latitude and mean July temperature (in degrees…

Q: We have data on Lung Capacity of persons and we wish to build a multiple linear regression model…

A: Given Information: Consider the partial result from STATISTICA.

Q: Consider the equation of the regression line y = 25 - 2.5x and ỹ = 12, %3D Find y when x 6 assuming…

A: Regression line isy=25-2.5xand y = 12

Q: Presidents and first ladies: The following table presents the ages of 9 U.S. presidents and their…

A: We have given that, Her agr (X) :- 45, 54, 45, 55, 59, 49, 56, 56, 31 His age (Y) :- 47, 54, 46,…

Q: if an estimated regression line has a y-intercept of 10 and a slope of -4, then when x=2, what is…

A: It is given that, An estimated regression line has y-intercept ,a= 10 Slope,b=-4 Thus,The estimated…

Q: A data set consists of the following ordered pairs: {(0, 8), (2, 11), (6, 17), (8, 20), (9,…

A: Consider the following table: There are 5 data set pairs given. Thus, n =5.

Q: The US government is interested in understanding what predicts death rates. They have a set of data…

A: Identify the correct option for which of the variables has negative correlation with the deaths. The…

Q: Suppose that a simple linear regression model is appropriate for describing the relationship between…

A: Given data in the problem isthe true regression line is y = 22500 + 43x σ = 5000We have to…

Q: The United States gross national product, in trillions of dollars, is given in the table below. Date…

A: The table for United states gross national product, in trillion of dollars is shown Year Gross…

Q: Price of eggs and milk: The following table presents the average price in dollars for a dozen eggs…

A: Given that By using excel regression the values are obtained below

Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day)
imported by a country, for the last seven years. Construct and interpret a 90% prediction interval for the amount of crude oil imported by the this country when the
amount of crude oil produced by the country is 5,464 thousand barrels per day. The equation of the regression line is y = - 1.166x + 16,080.356.
Oil produced, x
Oil imported, y
5,849
5,734
5,603
5.406
5.152
5,076
5,050
9,328
9,114
9,600
10,072
10,190
10,119
10,002
Construct and interpret a 90% prediction interval for the amount of crude oil imported when the amount of crude oil produced by the country is 5,464 thousand barrels
per day. Select the correct choice below and fill in the answer boxes to complete your choice.
(Round to the nearest cent as needed.)
O A. There is a 90% chance that the predicted amount of oil imported is between
and
thousand barrels, when there are 5,464 thousand barrels produced.
O B. We can be 90% confident that when the amount of oil produced is 5,464 thousand barrels, the amount of oil imported will be between
and

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

Step 2

Step 3

Step 4

Step 5

Trending now

This is a popular solution!

Step by step

Solved in 5 steps with 4 images

SEE SOLUTION Check out a sample Q&A here

Knowledge Booster

$Correlation, Regression, and Association$

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

The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1x�^=�0+�1�. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 7171 6262 7878 9494 8383 8181 8080 9494 8585 6262 Grades on Final 8888 7979 8888 9191 8080 7070 7171 9393 6565 7777
The number of initial public offerings of stock issued in a 10-year period and the total proceeds of these offerings (in millions) are shown in the table. The equation of the regression line is y = 46.360x + 18,657.31. Complete parts a and b 412 455 Issues, x. Proceeds, 17,955 27,527 43,371 30,734 66,292 65,063 22,264 11,783 31,116 27,537 685 476 483 384 54 75 194 170 (a) Find the coefficient of determination and interpret the result. (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? The coefficient of determination is the fraction of the variation in proceeds that is unexplained and is due to other factors or sampling error. The remaining fraction of the variation is explained by the variation in issues. The coefficient of determination is the fraction of the variation proceeds that can be explained by the variation in issues. The remaining fraction of the variation is unexplained and is due to other factors or to sampling error. (b)…
The following table gives the data for the grades on the midterm exam and the grades on the final exam. Determine the equation of the regression line, yˆ=b0+b1xy^=b0+b1x. Round the slope and y-intercept to the nearest thousandth. Grades on Midterm and Final Exams Grades on Midterm 78 63 85 92 82 89 69 89 83 61 Grades on Final 77 75 88 92 86 86 80 85 77 63
The table below shows the amounts of crude oil (in thousands of barrels per day) produced by a country and the amounts of crude oil (in thousands of barrels per day) imported by a country, for the last 7 years. Construct and interpret a 98% prediction interval for the amount of oil imported by the country and the amount of oil produced by the country is 5,483 thousand barrels per day. The equation of the regression line is y = -1.194x + 16,234.906
Substitute the values you found in steps 1 and 2 into the equation for the regression line to find the estimated linear model. According to this model, if the value of the independent variable is increased by one unit, then find the change in the dependent variable yˆy^. hour studyings 1 2 4 5 6 midterm grades 62 65 73 75 81
The table below shows the average weekly wages (in dollars) for state government employees and federal government employees for 10 years, construct and interpret a 98% prediction interval for the average weekly wages of federal government employees when the average weekly wages of state government employees is $888 the equation of the regression line is y= 1.453x-47.386. Wages(state), X | 739|760|784|822|898|921|937|954|965| Wages (federal), Y |1,036|1,054|1,105|1,136|1,192|1,253|1,266|1,327|1,400|
The table shows the numbers of new-vehicle sales (in thousands) in the United States for Company A and Company B for 10 years. The equation of the regression line is y = 0.991x + 1,222.81. Complete parts (a) and (b) below. New-vehicle sales (Company A), x New-vehicle sales (Company B), y 4,149 3,923 3,566 3,400 3,266 3,076 2,868 2,485 1,952 2,066 4,912 4,871 4,827 4,721 4,672 4,474 4,684 3,822 2,956 2,754 (a) Find the coefficient of determination and interpret the result. r² = r2 = 0.821 (Round to three decimal places as needed.) How can the coefficient of determination be interpreted? The coefficient of determination is the fraction of the variation in new-vehicle sales for Company B that can be 2 explained by the variation in new-vehicle sales for Company A and is represented by The remaining fraction of the variation, 1-2, is unexplained and is due to other factors or to sampling error. s (b) Find the standard error of estimates and interpret the result. Se O (Round to three decimal…
The equation used to predict college GPA (range 0-4.0) is y = 0.17 +0.51x, +0.002x,, where x, is high school GPA (range 0-4.0) and x, is college board score (range 200-800). Use the multiple regression equation to predict college GPA for a high school GPA of 3.8 and a college board score of 500. The predicted college GPA for a high school GPA of 3.8 and a college board score of 500 is (Round to the nearest tenth as needed.)
Using a sample of recent university graduates, you estimate a simple linear regression using initial annual salary as the dependent variable and the graduate's weighted average mark (WAM) as the explanatory variable. If the regression model has an estimated intercept of 3200 and an estimated slope coefficient of 550, what is the predicted starting salary of a student with a WAM of 64?
Find the least-squares regression line treating square footage as the explanatory variable. y = (Round the slope to three decimal places as needed. Round the intercept to one decimal place as needed.)
Find the regression equation, letting the first variable be the predictor (x) variable. Using the listed lemon/crash data, where lemon imports are in metric tons and the fatality rates are per 100,000 people, find the best predicted crash fatality rate for a year in which there are 425 metric tons of lemon imports. Is the prediction worthwhile? Lemon Imports Crash Fatality Rate 226 270 16 15.8 364 481 521 15.5 15.4 14.9
Select all the charts that violate the conditions for linear regression. These are residual plots so the red line represents the average residual, zero. 미 Od (a) (d) 매 Get help: Video (b) (e) (c) (1)