Using the linear correlation coefficient found in the previous step, determine whether there is sufficient evidence to support the claim of a linear correlation between the two variables. Choose the correct answer below.
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- The relationship between two variables partialling out the effect that a third variable has on one of those variables can be expressed using a: a. Partial correlation O b. Point-biserial correlation Oc. Semi-partial correlation Od. Bivariate correlationThe table below includes data from taxi rides. The distances are in miles, the times are in minutes, the fares are in dollars, and the tips are in dollars. Is there sufficient evidence to conclude that there is a linear correlation between the time of the ride and the tip amount? 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 time of the ride and the tip amount. Does it appear that riders base their tips on the time of the ride? Use a significance level of a=0.05. Click the icon to view the data on taxi rides. Construct a scatterplot. Choose the correct graph below. OA. 10- Time of the ride (minutes) The linear correlation coefficient is r= (Round to three decimal places as needed.) Taxi data B. C. G 40 Time of the ride (minutes) Time of the ride (minutes) Full data set Time Fare Tip Distance 0.29 2.64 10.84 14.05 1.12 1.58 1.12…For a data set of chest sizes (distance around chest in inches) and weights (pounds) of seven anesthetized bears that were measured, the linear correlation coefficient is r = 0.715. 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? Click the icon to view the table of critical values of r. The critical values are (Type integers or decimals. Do not round. Use a comma to separate answers as needed.) Since the correlation coefficient r is in the right tail above the positive critical value, there is sufficient evidence to support the claim of a linear correlation. Table of Critical Values of r - X Number of Pairs of Data n Critical Value of r 4 0.950 5 0.878 6 0.811 7 0.754 8 0.707 9 0.666 10 0.632 11 0.602 12 0.576 Print Done ×
- identify the linear correlation coefficient r, test statistics and p value.Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths, foot lengths, and heights of males. 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. Based on these results, does it appear that police can use a shoe print length to estimate the height of a male? Use a significance level of α=0.01. Shoe Print (cm) 29.0 29.0 31.2 31.7 27.1 Foot Length (cm) 26.3 24.9 28.0 26.0 25.7 Height (cm) 177.5 173.1 181.1 181.6 176.9find the linear correlation coefficent and the critical value(s)
- X is a normally distributed variable with µ=125 and s=10. If we take a SRS of size 25, find: P(X<126) P(< 126)This question has 4 parts, Thank you.Police sometimes measure shoe prints at crime scenes so that they can learn something about criminals. Listed below are shoe print lengths, foot lengths, and heights of males. 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. Based on these results, does it appear that police can use a shoe print length to estimate the height of a male? Use a significance level of a=0.05. Shoe Print (cm) 28.8 28.8. 32.1 32.6 Foot Length (cm) Height (cm) 25.2 181.7 24.9 173.5 27.5 27.6 27.5 25.9 186 169.1 171 Construct a scatterplot. Choose the correct graph below. OA. 200- 2 160+ Shoe Print (cm) 35 The linear correlation coefficient is r= (Round to three decimal places as needed.) B. 200- 160- 25 Shoe Print (cm) ○ C. 200- G 35 160+ 25 Shoe Print (cm) 35 OD. Q 200- Height (cm) G 160- 25 35 Shoe Print (cm)
- For a sample of eight bears, researchers measured the distances around the bears' chests and weighed the bears. Minitab was used to find that the value of the linear correlation coefficient is r = 0.862. Using a = 0.05, determine if there is a linear correlation between chest size and weight. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? Click here to view a table of critical values for the correlation coefficient. a. Is there a linear correlation between chest size and weight? O A. No, because the absolute value of r exceeds the critical value of 0.707. O B. Yes, because r falls between the critical values of -0.707 and 0.707. O C. Yes, because the absolute value of r exceeds the critical value of 0.707. O D. The answer cannot be determined from the given information. b. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? (Round to three decimal…Please answer all sectionsThe 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…