A set of data with a correlation coefficient of -0.55 has a a) moderate negative linear correlation Ob) weak negative linear correlation Oc) strong negative linear correlation O d) little or no linear correlation
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- The 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 the two variables. Use a significance level of α = 0.01. Does it appear that riders base their tips on the time of the ride? Click here for information on the taxi rides. Construct a scatterplot. Choose the correct graph below. OA. 25 은 Q Q 0+ 0 35 Ride time (minutes) Determine the linear correlation coefficient. The linear correlation coefficient is r= (Round to three decimal places as needed.) &B. 25- Q 0- bro 0 35 Ride time (minutes) Taxi data Distance 0.63 6.00 6.30 1.89 Time Fare Tip C... 2.44 18.00 14.30…A pediatrician wants to determine the relation that may exist between a child's height and head circumference. She randomly selects 8 children, measures their height and head circumference, and obtains the data shown in the table. The pediatrician wants to use height to predict head circumference. Compute the linear correlation coefficient between the height and head circumference of a child. Height Head Circumference (inches) (inches) 27.5 25 (Round to three decimal places as needed.) 17.3 17.1 26 25.25 27.25 26.75 25.75 27 25 17.2 17 17.6 17.4 17.2 17.3 Enter your answer in the answer box and then click Check Answer. All parts showing Clear All Check Answer Type here to search TOUG Panasonic CF-54 CDSS-4852 TERMO TOGA O O O O D () Scre Loc PrtSc Num Lock F10 F11 F12 F7 F8 F9 SysRq F5 F6 F3 F4 A 8 F1 F2 Esc & 7 0 8 B 90 5 A2 24 近 %#3A) Positive correlation B) Negative correlation C) No correlation
- Compute the linear correlation coefficient. The linear correlation coefficient for the four pieces of data isThe 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 the two variables. Use a significance level of α=0.01. Does it appear that riders base their tips on the time of the ride? Choose the correct graph below (attached image) Determine the linear correlation coefficient. The linear correlation coefficient is r=_____ (Round to three decimal places as needed.) Determine the null and alternative hypotheses. H0: ρ ▼ greater than> equals= not equals≠ less than< enter your response here H1: ρ ▼ equals= not equals≠ less…There is a strong positive linear correlation between the number of clear days and the height of bean plants. Does this mean that more clear days cause the bean plants to grow taller? A. Yes. Since the number of clear days and height are positively correlated, this means a greater number of clear days causes the bean plants to grow taller. B. No. Any number of factors could also affect the height of the bean plants. C. No. Since the number of clear days and height are linearly correlated, this means a smaller number of clear days causes the bean plants to grow taller. D. Yes. Since the number of clear days and height are linearly correlated, this means a greater number of clear days causes the bean plants to grow taller.
- 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= 0.01. Shoe Print (cm) | 28.8 Foot Length (cm) 24.8 Height (cm) 30.8 30.4 31.1 28.6 24.6 27.8 26.1 25.3 177.6 179.2 179.2 169.4 169.5Suppose data are collected concerning the weight of a person in pounds and the number of calories burned in 30 minutes of walking on a treadmill at 3.5 miles per hour. How would the value of the correlation coefficient, r, change if all of the weights were converted to kilograms?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…After gathering data about the number of starfish and measuring the pollution in areas of the ocean you find a negative linear correlation between pollution levels and number of starfish. What can you conclude based on this information? a. There is a confounding variable that is affecting both pollution and starfish. b. As pollution rises the number of starfish falls c. That pollution is causing starfish to die, leading to the negative correlation d. That pollution is supporting starfish, leading to the negative correlation