KListed 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 ofthe 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 betweenoverhead widths of seals from photographs and the weights of the seals?GA300Aweight (kg)tumI AL HAT DERTHE PHOOverhead WidthWeightClick here to view a table of critical values for the correlation coefficient.1007width (cm)107.1115Q7.51729.8248B.300-The linear correlation coefficient is r=(Round to three decimal places as needed.)9.3 8.8196 202Aweight (kg)100-2DH8.2 D188width (cm)BECKHC.300Aweight (kg)100-width (cm)10D.Aweight (kg)300-19+10041totewidth (cm)10QG

Given information: Overhead Width(x) Weight(y) x^2 y^2 xy 7.1 115 50.41 13225 816.5 7.5 172…

Answered: Listed below are the overhead widths…

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 paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit . Use a significance level of 0.05 and round all values to 4 decimal places. Advertising Cost Profit 3 19 4 16 24 6 29 7 25 27 10 30 Ho: p = 0 На: р * 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is O Less than (or equal to) a O Greater than a The p-value leads to a decision to O Do Not Reject Ho O Accept Ho O Reject Ho The conclusion is O There is a significant negative linear correlation between advertising expense and profit. O There is a significant linear correlation between advertising expense and profit. O There is a significant positive linear correlation between advertising expense and profit. O There is insufficient evidence to make a conclusion about the linear correlation between advertising expense and…
what are the critical values r =?
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The Minitab output shown below was obtained by using paired data consisting of weights (in lb) 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 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 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. The linear correlation coefficient is (Round to three decimal places as needed.) Is there sufficient evidence to support a claim of linear correlation? Yes O No Minitab output The regression equation is Highway = 50.8 -0.00508 Weight Predictor Coef SE Coef T P Constant 50.772 2.793…
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…
Can you please check my work
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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