For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of five types of automobile, the linear correlation coefficient is found and the P value is 0.027. Write a statement that interprets the P-value and includes a conclusion about linear correlation. v so there V sufficient evidence to The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is %, which is conclude that there is a linear correlation between weight and highway fuel consumption in automobiles. (Type an integer or a decimal. Do not round.)

For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of five types of automobile, the linear correlation coefficient is found and the P value is 0.027. Write a statement that interprets the P-value and includes a conclusion about linear correlation. v so there V sufficient evidence to The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is %, which is conclude that there is a linear correlation between weight and highway fuel consumption in automobiles. (Type an integer or a decimal. Do not round.)

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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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)
What is the correlation coefficient (r) for the best data set
will this be sufficient or is not sufficient evidence.
An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height. To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated. Identify the correct null hypothesis A. H0: There is no relationship between leg power and jump height B. H0: There is a relationship between leg power and jump height C. HA: There is a relationship between leg power and jump height D. HA: There is no relationship between leg power and jump height
An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height. To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated. What does this type of correlation indicate about how leg strength and jump height change together? A. Both leg strength and jump height increase and decrease together B. There is no relationship between leg strength and jump height C. As leg strength increases, jump height decreases D. As jump height increases, leg strength decreases
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 a = 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. O A. Tip Amount ($) 25- Q 0 35 G Ride time (minutes) Determine the linear correlation coefficient. The linear correlation coefficient is r= (Round to three decimal places as needed.) Tip Amount ($) B. 25- 0- 0 35 G Ride time (minutes) Taxi data ip Amount (S C. 25- 0- 35 Ride time…
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 25.3 177.6 179.2 179.2 169.4 169.5
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) Foot Length (cm) Height (cm) Height (cm) 160- 25 Shoe Print (cm) 30.1 25.7 179 35 0 30.1 32.4 32.8 25.1 27.5 27.1 176.9 187.3 170.8 The linear correlation coefficient is r= 0.495 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: p = H₁: P 0 (Type integers or decimals. Do not round.) The test statistic is t = 0.99. (Round to two decimal places as needed.) The P-value is (Round to three…
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…
An exercise scientist wants to know if there is a relationship between explosive leg power and standing jump height. To determine if a relationship exists, a group of 30 participants' (N = 30) Leg power was measured by recording each participants' single squat weight max (in pounds). Next, each participant was asked to perform a standing jump and their Jump height was recorded (in meters). Using the variables “Leg power” and “Jump height”, conduct a Pearson's Correlation, at α = 0.05, to determine if leg power and jump height are correlated Interpret r. What type of correlation exists between leg strength and jump height? A. A negative correlation B. No correlation C. A positive correlation D. We cannot know based on the available information
For a data set of weights (pounds) and highway fuel consumption amounts (mpg) of five types of automobile, the linear correlation coefficient is found and the P-value is 0.033. Write a statement that interprets the P-value and includes a conclusion about linear correlation. The P-value indicates that the probability of a linear correlation coefficient that is at least as extreme is nothing%, which is ▼ high, low, so there ▼ is not is sufficient evidence to conclude that there is a linear correlation between weight and highway fuel consumption in automobiles.