nehip:aer:eC,CFifty-four wild bears were anesthetized, and then their weights and chest sizes weremeasured and listed in a data set. Results are shown in the accompanying display. Isthere sufficient evidence to support the claim that there is a linear correlation between theweights of bears and their chest sizes? When measuring an anesthetized bear, is it easierto measure chest size than weight? If so, does it appear that a measured chest size canbe used to predict the weight? Use a significance level of α = 0.05.Determine the null and alternative hypotheses.Ho: PH₁: p▼(Type integers or decimals. Do not round.)Get more help.(99+TRUSIONST Correct 03 TOC...SECorrelation ResultsCorrelation coeff, r: 0.960762Critical r:+0.2680855P-value (two tailed): 0.000Clear allNAS...4Check answer5:59 PM7/11/2022E20

The following information has been given: Correlation coefficient r=0.960762 Critical value…

Answered: Correlation Results Fifty-four wild…

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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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 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 a measured chest size can be used to predict the weight? Use a significance level of a = 0.05 Question: Determine the null and alternative hypotheses
Baseball owners believe that the more runs scored, the higher the attendance. Is there evidence that more fans attend games if the teams score more runs? Data collected midway through the season indicate a correlation of 0.848 between runs scored and the number of people at games. a) Does the scatterplot indicate that it's appropriate to calculate a correlation? Explain. O A. Yes, because the relationship between number of runs scored and attendance appears to be straight. O B. Yes, because the association between the number of runs scored and attendance is positive. 37500- OC. No, because there are too many outliers for a numerical correlation to be appropriate. 30000- O D. No, because the number of runs scored and attendance are not quantitative variables. b) Describe the association between attendance and runs scored. 22500- 320 360 400 440 480 O A. The association between attendance and runs scored is negative, straight, and moderate. Runs O B. The association between attendance…
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 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 a measured chest size can be used to predict the weight? Use a significance level of α=0.05. Correlation Results Correlation coeff, r: 0.979514 Critical r: ±0.2680855 P-value (two tailed): 0.000 Determine the null and alternative hypotheses. H0: ρ(>,≠,=,<) ________ H1: ρ (>,≠,=,<) ________ (Type integers or decimals. Do not round.) Identify the correlation coefficient, r. r=_____ (Round to three decimal places as needed.) Identify the critical value(s). (Round to…
Online clothes An online clothing retailer keeps trackof its customers’ purchases. For those customers who signed up for the company’s credit card, the com-pany also has information on the customer’s Age and Income. A random sample of 500 of these customers shows the following scatterplot of Total Yearly Pur-chases by Age:The correlation between Total Yearly Purchases and Age isr = 0.037. Summary statistics for the two variables are: a) What is the linear regression equation for predictingTotal Yearly Purchase from Age?b) Do the assumptions and conditions for regressionappear to be met?c) What is the predicted average Total Yearly Purchasefor an 18-year-old? For a 50-year-old? d) What percent of the variability in Total Yearly Pur-chases is accounted for by this model? e) Do you think the regression might be a useful one forthe company? Explain.
The line of best fit and the correlation coefficient are calculated for a set of data. The value of the correlation coefficient is r=0.10. What is the strength and type of the correlation for this data? a) weak and positive b) strong and negative c) strong and positive d) weak and negative
Many people believe that crime rate declines with age. a) Use the data below to verify whether this is true using a scatterplot. b) Is the relationship between crime rate and age strong, medium, or weak? c) Can the correlation coefficient be used to measure the extent to which crime rate is related to age? E Click the icon to view the data. a) Choose the correct scatterplot below. O A. O B. OC. OD. 20,000- 20,000- 20,000- 20,000- 0- Age Age Age Age Does it appear that the crime rate declines with age? O A. The crime rate tends to gradually increase with age. B. The crime rate tends to increase until adulthood, after which it gradually declines. OC. The crime rate tends to increase until middle age, after which it gradually declines. O D. The crime rate tends to gradually decrease with age. b) Is the relationship between crime rate and age strong, medium, or weak? O A. The scatterplot appears to show a medium relationship. B. The scatterplot appears to show a weak relationship. O C. The…
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…
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 data in the table below show years of teaching experience and annual salary in dollars for 12 randomly selected mathematics instructors in Illinois colleges/ universities for the 2013/2014 school year. Is there a linear correlation between a mathematics instructor’s years of experience and his or her annual salary? Number of Years:7 9 6 7 11 12 11 3 3 7 9 1 Salary (in Dollars): 48,897 62,866 54,585 56,611 53,541 53,541 47,027 47,970 46,668 48,029 46,735 45,000
Five students provided data regarding the number of hours they spent on studying (TimeStudy) and their GPA. The data are as follows. Answer the following questions. TimeStudy GPA Student 1 2.00 3.50 Student 2 4.00 3.70 Student 3 5.00 3.30 Student 4 3.00 2.60 Student 5 4.00 3.40 a) According to the SPSS table, what can you conclude regarding the correlation between TimeStudy and GPA? Report the conclusions in proper formats. b) By fitting a linear regression line to represent the relationship between TimeStudy and GPA, the regression line function is ??? = ?. ?? + ?. ?? × ?????????. See the figure Calculate (by hand) the SSresidual.
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 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 a measured chest size can be used to predict the weight? Use a significance level of α=0.05. Correlation Results Correlation coeff, r: 0.955111 Critical r: ±0.2680855 P-value (two tailed): 0.000 Determine the null and alternative hypotheses. H0: ρ less than< not equals≠ less than< greater than> equals= nothing H1: ρ

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