Critical r:Fifty-four wild bears were anesthetized, and then their weights and chest sizeswere measured and listed in a data set. Results are shown in the accompanyingdisplay. Is there sufficient evidence to support the claim that there is a linearcorrelation between the weights of bears and their chest sizes? When measuringan anesthetized bear, is it easier to measure chest size than weight? If so, does it P-value (two tailed): 0.000appear that a measured chest size can be used to predict the weight? Use asignificance level of a = 0.05.OA. There is one critical value at r=B. There are two critical values at r= ± 0.268Correlation ResultsCorrelation coeff, r: 0.964493+0.2680855Is there sufficient evidence to support the claim that there is a linear correlation between the weights of bears and theirchest sizes? Choose the correct answer below and, if necessary, fill in the answer box within your choice.(Round to three decimal places as needed.)OA. Yes, because the absolute value of the test statistic exceeds the critical value.B. Yes, because the test statisticC. No, because the test statisticfalls between the critical values.D. No, because the absolute value of the test statistic exceeds the critical value.O E. The answer cannot be determined from the given information.falls between the critical values.

Correlation ResultsCorrelation coefficient r : 0.964493 Critical r : ±0.2680855P-value (two…

Answered: Fifty-four wild bears were…

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 amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.01. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) Tip (dollars) 31.80 52.94 85.82 102.16 60.17 111.77 D 5.46 6.07 15.82 15.40 11.15 20.32 Construct a scatterplot. Choose the correct graph below. O A. O B. Oc. D. Q 25- 25- 25 0- 30 0- 30 Bill Amount ($) 0+ 30 Bill Amount (S) 0- 30 Bill Amount (S) 120 120 120 Bill Amount (S) 120 The linear correlation coefficient is r= 0.954 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: p H,: P (Type integers or decimals. Do not round.) Tip Amount ($) ip Amount ($) Tip Amount ($) Tip Amount ($)
A) Find the correlation coefficient , rounded to the nearest 10th. B) What percent of the variability in static weight can be explained by the linear model? Round to the nearest 10th. C) Using the predictive model suggested, what would the static weight of a truck be if its weight in motion was 28,000 pounds?
In running a Pearson correlation, you notice that there are a few outliers. Please describe the next course of action, if any, for the dataset and explain your reasoning.
Which set of data would probably show a strong positive linear correlation? a) the number of defective light bulbs produced and the time of the day when they were manufactured b) marks on a history test and the heights of the students c) the colour of cars sold and the annual income of the car buyers d) the height of corn in a field and the amount of precipitation during the growing season acer
In a study examining the relation of math ability to the belief that math ability was innate, the belief was considered the predictor variable. The researcher hopes to find a correlation between the participants’ math ability and their belief that math ability is innate. The scores for the three participants are shown below. The group that believed that math is NOT innate scored 66, 70, 50. The group that believed that math IS innate scored 7, 4,10. Calculate, by hand, the correlation between these two variables. Is it positive or negative and is it a strong correlation?
Which set of data would probably show a strong positive linear correlation? a) the number of defective light bulbs produced and the time of the day when they were manufactured b) marks on a history test and the heights of the students c) the colour of cars sold and the annual income of the car buyers d) the height of corn in a field and the amount of precipitation during the growing season
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technologgy was also given a foot length of 10.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 10.8 cm, what is the single value that is the best predicted height for that person? H Click the icon to view the technology output. The single value that is the best predicted height is cm. Technology Output (Round to the nearest whole number as needed.) The regression equation is Height - 67.5 +5.15 Foot Length Predictor Coef SE Coef Constant 67.52 11.07 6.10 0.000 Foot Length 5.1508 0.4817 10.69 0.000 S-5.50271 R-Sq = 73.18 R-Sq (adj) = 72.44 Predicted Values for New Observations New Obs Fit SE Fit 95 CI 954 PI 123.149 1.605 (119.732, 126.566) (111.996, 134.302) Values of Predictors for New…
A study of elementary school children, ages 6 to 11, finds a high positive correlation between shoe size x and score y on a test of reading comprehension. The observed correlation is most likely due to: the effect of a lurking variable, such as age or years of reading experience. a mistake, because the correlation must be negative. cause and effect (larger shoe size causes higher reading comprehension). reverse cause and effect (higher reading comprehension causes larger shoe size).
Fifty-four wild bears were anesthetized, and then their weights and chest sizes were measured and listed in a data set. Results are shown in the accompanying display. Is there sufficient evidence to support Correlation Results the claim that there is a linear correlation between the weights of bears and their chest sizes? When measuring an anesthetized bear, is it easier to measure chest size than weight? If so, does it appear that Correlation coeff, r: 0.959614 a measured chest size can be used to predict the weight? Use a significance level of = 0.05. Critical r: +0.2680855 P-value (two tailed): 0.000 Но: Р H1:P (Type integers or decimals. Do not round.) Identify the correlation coefficient, r. (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) O A. There is one critical value at r= . B. There are two critical values at r= ± Is there sufficient evidence to support the claim that there is a linear correlation between…
The accompanying technology output was obtained by using the paired data consisting of foot lengths (cm) and heights (cm) of a sample of 40 people. Along with the paired sample data, the technology was also given a foot length of 17.8 cm to be used for predicting height. The technology found that there is a linear correlation between height and foot length. If someone has a foot length of 17.8 cm, what is the single value that is the best predicted height for that person? Click the icon to view the technology output. The single value that is the best predicted height is (Round to the nearest whole number as needed.) cm. Technology Output The regression equation is Height = 53.3+4.25 Foot Length Predictor Constant Coef SE Coef 53.28 11.44 Foot Length 4.2537 0.4699 S = 5.50739 R-Sq=72.3% R-Sq (adj) = 71.6% T 4.66 9.05 Predicted Values for New Observations New Obs 1 Fit SE Fit 128.996 1.733 (124.309, 133.683) 95% CI Foot New Obs Length 1 17.8 0.000 0.000 Values of Predictors for New…
The National Football League (NFL) records a variety of performance data for individuals and teams. To investigate the importance of passing on the percentage of games won by a team, the following data show the average number of passing yards per attempt (Yds/Att) and the percentage of games won (WinPct) for a random sample of 10 NFL teams for the 2011 season (NFL website). Team Yds/Att WinPct 5.7 26 Arizona Cardinals Atlanta Falcons Carolina Panthers 7.6 67 7.3 52 6.9 51 Chicago Bears Dallas Cowboys 5.1 17 8.6 82 New England Patriots Philadelphia Eagles Seattle Seahawks 5.3 21 6.6 41 St. Louis Rams 6.5 41 Tampa Bay Buccaneers. 6.1 38 a. Choose the correct a scatter diagram with the number of passing yards per attempt on the horizontal axis and the percentage of games won on the vertical axis. B. A. WinPct WinPct 80 DD J F1 70- 60- 50+ -40- 30 20- F2 80 F3 000 000 F4 F5 80- -70 60- 50- 40- 30- 20- S F6 ● - F7 DII F8 F9 F10 () F11 <))) F12 A
Listed below are amounts of bills for dinner and the amounts of the tips that were left. Construct a scatterplot, find the value of the linear correlation coefficient r, and find the P-value of r. Determine whether there is sufficient evidence to support a claim of linear correlation between the two variables. Use a significance level of a = 0.05. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) Tip (dollars) 69 Construct a scatterplot. Choose the correct graph below. O A. 25- 04 30 1.6 Bill Amount (S) 30.39 49.64 84.71 94.16 62.06 101.95 6.07 8.67 11.03 12.99 9.31 13.46 120 Q ✔ The linear correlation coefficient is r= (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: P H₁: p (Type integers or decimals. Do not round.) The test statistic is t = (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value of the linear correlation…

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