An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide (CO₂)emissions. 10 countries were sampled. The correlation between GDP and carbon dioxide emissions is r=0.912. Is the correlation significant at a=.05?Give the critical value:Is the correlation significant? (yes or no)CO2 emissions(in millions of metric tons)12001000800600400200-||1234 5GDP (in trillions of dollars)6X

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Answered: An economist wants to determine whether…

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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At Burnt Mesa Pueblo, archaeological studies have used the method of tree-ring dating in an effort to determine when prehistoric people lived in the pueblo. Wood from several excavations gave a mean of (year) 1242 with a standard deviation of 35 years. The distribution of dates was more or less mound-shaped and symmetric about the mean. Use the empirical rule to estimate the following. a) a range of years centered about the mean in which about 68% of the data (tree-ring dates) will be found between "BLANK" and "BLANK" A.D. b) a range of years centered about the mean in which about 95% of the data (tree-ring dates) will be found between "BLANK" and "BLANK" A.D. c) a range of years centered about the mean in which almost all the data (tree-ring dates) will be found between "BLANK" and "BLANK" A.D.
n For a data set of chest sizes (distance around chest in inches) and weights (pounds) of four anesthetized bears that were measured, the linear correlation coefficient is r= 0.996. Use the table available below to find the critical values of r. Based on a comparison of the linear correlation coefficient r and the critical values, what do you conclude about a linear correlation? Click the icon to view the table of critical values of r. The critical values are (Type integers or decimals. Do not round. Use a comma to separate answers as needed.) Table of Critical Values of r Number of Pairs of Data n 4 5 6 7 89O12 10 11 Critical Value of r 0.950 0.878 0.811 0.754 0.707 0.666 0.632 0.602 0.576 X
For the accompanying data set, (a) draw a scatter diagram of the data, (b) compute the correlation coefficient, and (c) determine whether there is a linear relation between x and y. Click the icon to view the data set. Click the icon to view the critical values table. critical values for the correlation coefficient Critical values for Correlation CoETTIcient (a) Draw a scatter diagram of the data. Choose the correct graph below. 3 0.997 4 0.950 A. В. 0.878 Ay 10- Ay 10- 0.811 7 0.754 8 0.707 9 0.666 10 0.632 11 0.602 12 0.576 13 0.553 14 0.532 15 0.514 16 0.497 17 0.482 18 0.468 19 0.456 20 0.444 21 0.433 22 0.423 23 0.413 24 0.404 25 0.396 26 0.388 27 0.381 28 0.374 29 0.367 30 0.361 0+ 0- 10 10 (b) Compute the correlation coefficient. The correlation coefficient is r= |: (Round to three decimal places as needed Data set X 2 6. 7 9. y 7 6. 9. Print Done Co
A researcher was interested in the relationship between number of close friends and self-esteem. A sample of 40 participants were recruited and asked to report the number of close friends they had, as well as their level of self-esteem. The data showed a positive correlation, such that having more close friends was associated with having higher self-esteem, r(38) = .45. Here are the descriptive statistics for the two variables: Close Friends Self-Esteem Mean 8.90 5.20 SD 3.75 2.15 In a regression equation predicting self-esteem, what is the value of b?A) 0.258B) 0.263C) 0.785D) 0.573 In a regression equation predicting self-esteem, what is the value of a?A) -1.787B) 7.496C) 2.904D) 4.818 One participant named Jesse reported that they had 4 close friends. Based on the regression equation, what would Jesse’s predicted self-esteem score be?A) 3.936B) 1.353C) 7.958D) 8.528 If Jesse’s actual self-esteem score was 5, what is the residual score?A) -2.958B) 3.647C) -3.528D)…
Using the following information select the appropriate interpretation for the correlation coefficient: Variables being compared are age in years and annual salary. r = -0.15 A. It indicates a weak positive correlation which implies, as age increases annual salary decreases B. It indicates a strong negative correlation which implies, as age increases annual salary decreases C. It indicates a strong positive correlation which implies, as age increases annual salary also increases D. It indicates a weak negative correlation which implies, as age increases annual salary decreases
A researcher wanted to know the relationship between sales per 24h in a department store, the amount of rain that day (in mm) and the mean age of 1000 customers. The SPSS output is presented below. What is the correct way to report the correlation between sales per 24h and rainfall that day in APA style? Question 24 options: r(16) = -.909, p<.001 r(18) = -.909, p=.000 r(18) = -.909, p<.001 r(16) = -.909, p=.000
For each of a number of cities across Canada, the number of people with Cantonese as a mother tongue and the number of people with Mandarin as a mother tongue were rocorded. A scatterplot of the data is shown in the figure below. The correlation between the number of Cantonese speakers in a city aud the number of Mandarin speakers is 0.980. Do you think this correlation is a reasonable summary of the relationship? Why, or why not? (a) If the two largest cities (Toronto and Vancouver) were removed, the correlation would be even higher. (b) No, because there are outliers and/or influential points. (c) Yes, because the relationship is more or less linear. (d) No, because the relationship is clearly curved. (e) Yes, because there are no influential points.
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The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.707. At & = 0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho:p = 0 Ha:p # 0 Determine the critical value(s). to = (Round to three decimal places as needed. Use a comma to separate answers as needed.)
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For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of twelve types of automobile, the linear correlation coefficient is found and the P-value is 0.009. Write a statement that interprets the P-value and includes a conclusion about linear correlation.
The weights (in pounds) of 6 vehicles and the variability of their braking distances (in feet) when stopping on a dry surface are shown in the table. Can you conclude that there is a significant linear correlation between vehicle weight and variability in braking distance on a dry surface? Use a = 0.05. Weight, x Variability in braking distance, y 5980 5370 6500 5100 5820 4800 1.72 1.97 1.87 1.63 1.64 1.50 Click here to view a table of critical values for Student's t-distribution. Setup the hypothesis for the test. Ho: Ha: P Identify the critical value(s). Select the correct choice below and fill in any answer boxes within your choice. (Round to three decimal places as needed.) O A. The critical value is. B. The critical values are - to and to %3D Calculate the test statistic. t= (Round to three decimal places as needed.) What is your conclusion? There enough evidence at the 5% level of significance to conclude that there a significant linear correlation between vehicle weight and…

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