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 Correlation Results 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 Correlation coeff, r: 0.956803 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. Critical r: 0.2680855 P-value (two tailed): 0.000 . . . Determine the null and alternative hypotheses. Ho: p = 0 H1: P # 0 (Type integers or decimals. Do not round.) Identify the correlation coefficient, r. r= 0.957 (Round to three decimal places as needed.) Identify the critical value(s). (Round to three decimal places as needed.) O A. There are two critical values at r= + O B. There is one critical value at r = 1.Refer to the accompanying scatterplot. a. Examine the pattern of all 10 points and subjectively determine whether there appears to be a strong correlation between x and y. Ay b. Find the value of the correlation coefficient r and determine whether there is a linear correlation. c. Remove the point with coordinates (9,1) and find the correlation 10-8 ... coefficient r and determine whether there is a linear correlation. d. What do you conclude about the possible effect from a single pair of values? Click here to view a table of critical values for the correlation coefficient. 10 a. Do the data points appear to have a strong linear correlation? O No Yes b. What is the value of the correlation coefficient for all 10 data points? r=(Simplify your answer. Round to three decimal places as needed.)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 231 265 357 484 533 Crash Fatality Rate 15.9 15.6 15.4 15.3 14.9 . . OA. Ho: P#0 B. Ho: P = 0 H1 : p = 0 H1: p# 0 O C. Ho: P = 0 OD. Ho: P= 0 H, : p >0 Hy: p