The Minitab output shown below was obtained by using paired data consisting of weights (in Ib) of 31 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 4000 lbto be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Giventhat there are 31 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts?Click the icon to view the Minitab display.Minitab outputThe linear correlation coefficient isThe regression equation is(Round to three decimal places as needed.)= 50.5 - 0.00594 WeightPredictorCoefSE CoefPConstant50.5442.97817.850.000Weight- 0.00593510.0007513- 7.280.000S= 2.10089R-Sq = 63.2%R- Sq(adj) = 60.6%Predicted Values for New ObservationsNewObsFitSE Fit95% CI95% PI126.8040.524(25.789, 27.819)(22.208, 31.400)Values of Predictors for New ObservationsNewObsWeight14000

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Answered: The Minitab output shown below was…

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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Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 228 264 358 482 531 15.9 15.7 15.5 15.3 14.9
The Minitab output shown below was obtained by using paired data consisting of weights (in lb) of 26 cars and their highway fuel consumption amounts (in mi/gal). Along with the paired sample data, Minitab was also given a car weight of 3000 lb to be used for predicting the highway fuel consumption amount. Use the information provided in the display to determine the value of the linear correlation coefficient. (Be careful to correctly identify the sign of the correlation coefficient.) Given that there are 26 pairs of data, is there sufficient evidence to support a claim of linear correlation between the weights of cars and their highway fuel consumption amounts? Click the icon to view the Minitab display. The linear correlation coefficient is (Round to three decimal places as needed.) Minitab output The regression equation is Highway = 50.3 -0.00539 Weight Predictor Coef SE Coef Constant 50.288 2.998 Weight -0.0053868 0.0007773 |S=2.11773 R-Sq=64.0% R-Sq(adj) = 60.9% Predicted Values…
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using a = 0.05, Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.1 7.5 178 Click here to view a table of critical values for the correlation coefficient. 9.6 9.4 8.8 8.2 Weight 112 205 238 204 188 OA. YB. OC. KD D. Aweight (kg) 300- A weight (kg) Aweight (kg) 300- Aweight (kg) 300- 300- .. 100 100+ 100 7. rect: 0 10 10 10 10 width (om) width (cm) width (on) widn (om) The linear correlation coefficient is r= (Round to three decimal places as needed.) Enter your answer in the answer box and then click Check Answer. O parts remaining Check Answer वी
For a data set of chest sizes (distance around chest in inches) and weights (pounds) of twelve anesthetized bears that were measured, the linear correlation coefficient is r= 0.732. 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?
Listed below are the overhead widths (in cm) of seals measured from photographs and the weights (in kg) of the seals. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the critical values of r using a = 0.01. Is there sufficient evidence to conclude that there is a linear correlation between overhead widths of seals from photographs and the weights of the seals? Overhead Width 7.2 7.5 9.8 9.3 8.9 8.1 Weight 119 172 248 201 205 181 Click here to view a table of critical values for the correlation coefficient. Construct a scatterplot. Choose the correct graph below. A. В. OC. D. Aweight (kg) 300- Aweight (kg) 300- Aweight (kg) 300- Aweight (kg) 300- 100+ 1004 100- 100+ 10 7 10 7 10 7 10 width (cm) width (cm) width (cm) width (cm) The linear correlation coefficient is r= (Round to three decimal places as needed.) The critical values are r= (Round to three decimal places as needed. Use a comma to separate answers as needed.) Because the absolute…
Complete the following instructions:i. Identify the independent and dependent variables.ii. Calculate and interpret the Pearson correlation coefficient r for the paired data. Be sure to indicate if the correlation is positive or negative, and whether it is strong, moderate, or weak, or if there does not appear to be any significant correlation. A researcher for a gasoline retailer examines the relationship between the volume of gasoline purchased in kL(i.e. 1000 L) compared to the price of gasoline (in $/L), over a course of several days, to see if there is a correlation between the data: Amount of Gasoline Purchased Price of Gasoline 2.257 1.079 3.126 1.015 2.793 1.046 4.671 0.973 2.137 1.021 5.916 0.939 2.775 0.995 4.88 0.927 3.162 0.964 7.498 0.899 2.971 0.982 3.596 0.945 1.372 1.129 3.961 1.059 i. Independent Variable: Dependent Variable: ii. Pearson correlation coefficient (r): Round to 3 decimal…
Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 228 266 358 484 531 15.8 15.7 15.5 15.2 14.8 O A. Ho: pz0 H4:p= 0 O B. Ho: p=0 H1:p 0 H1: p#0 Construct a scatterplot. Choose the correct graph below. OA. YB. Oc. OD. Ay 17- Ay 17- Ay 17- Ay 17- 16- Q 16- 16- 16- 15- 15- 15- 15- X 14- 14- 14- 14+ 200 400 600 200 400 600 200 400 600 200 400 600 The linear correlation coefficient is r= - 0.971 (Round to three decimal places as needed.) The test statistic is t= (Round to three decimal places as needed.)
A data set contains information on the grams of fat and number of calories in 25 different fast foods. The correlation coefficient between fat content and calories is determined to be 0.69. Calculate the p-value for the test of significance.
A data set contains information on the grams of fat and number of calories in 25 different fast foods. The correlation coefficient between fat content and calories is determined to be 0.62. Calculate the p-value for the test of significance.
Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value using a = 0.05. Is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate 231 265 358 483 530 15.8 15.7 15.5 15.2 14.8 What are the null and alternative hypotheses? OA. Ho: p 0 H₁ p=0 OC. Ho p=0 H₁: p>0 Construct a scatterplot. Choose the correct graph below. OA. Ay 17- 16- Q do ° 15- ° 14+ 0 200 400 600 The linear correlation coefficient is r= (Round to three decimal places as needed.) B. Ho: p=0 H₁p 0 OD. Ho: p=0 H₁: p<0 B. COD. Ay 17- Ay 17- Ay 17+ Q о 16- 16- 16- Q 0 ° ° 15- 15- ° G 15- G 14- 14- 14+ 0 200 400 600 0 200 400 600 0 200 400 600
Listed below are annual data for various years. The data are weights (metric tons) of imported lemons and car crash fatality rates per 100,000 population. Construct a scatterplot and find the value of the linear correlation coefficient r. Using a = 0.05, is there sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates? Do the results suggest that imported lemons cause car fatalities? Lemon Imports Crash Fatality Rate Construct a scatterplot. Choose the correct graph below. O A. ^) 17- 16- 15+ 14+ 0 0 8 Q O O O 200 400 600 Q 232 15.9 OB. Ay 17- 16- 15+ 14+ 0 -o q 264 15.6 0 200 400 600 Q ✔ 357 15.5 481 15.3 C O C. A) 17+ 16- 15- 14+ 534 14.9 O -0 0 200 400 The linear correlation coefficient r is. (Round to three decimal places as needed.) There sufficient evidence to conclude that there is a linear correlation between lemon imports and crash fatality rates. Do the results suggest that imported lemons cause car fatalities? O A.…
For a data set of brain volumes (cm3) and IQ scores of eleven males, the linear correlation coefficient is requals 0.883.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? The critical values are (Type integers or decimals. Do not round. Use a comma to separate answers as needed.)

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