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. 29.5 29.5 Shoe Print (cm) | 29.5 Foot Length (cm) 25.7 24.9 Height (cm) 32.3 27.1 180.7 178.4 189.7 178.8 27.4 D 24.5 169.9 32.7 26.4 Construct a scatterplot. Choose the correct graph below. O A. OB. В. C. OD. Q 200- 200 200- 200- 160+ 25 Shoe Print (cm) 160- 25 Shoe Print (cm) 160+ 25 Shoe Print (cm) 160+ 25 Shoe Print (cm) The linear correlation coefficient is r= 0.747 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: P V H:P Height (am)

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. 29.5 29.5 Shoe Print (cm) | 29.5 Foot Length (cm) 25.7 24.9 Height (cm) 32.3 27.1 180.7 178.4 189.7 178.8 27.4 D 24.5 169.9 32.7 26.4 Construct a scatterplot. Choose the correct graph below. O A. OB. В. C. OD. Q 200- 200 200- 200- 160+ 25 Shoe Print (cm) 160- 25 Shoe Print (cm) 160+ 25 Shoe Print (cm) 160+ 25 Shoe Print (cm) The linear correlation coefficient is r= 0.747 (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: P V H:P Height (am)

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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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 Crash Fatality Rate 266 15.7 228 358 484 531 15.8 15.5 15.2 14.8 What are the null and alternative hypotheses? O B. Ho: p=0 O A. Ho: p#0 H1:p=0 H1:p0 H,: p#0 Construct a scatterplot. Choose the correct graph below. OA. B. Oc. OD. Ay 17- Ay 17- AY 17- Ay 17- 16- Q 16- 16- 16- 15- 15- 15- 15- 14- 14+ 14- 14- 200 400 600 200 400 600 200 400 6ỏ0 200 400 600 The linear correlation coefficient is r= (Round to three decimal places as needed.)
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…
Find the line of best fit for the ordered pairs 11, 52 and13, 82. What is the correlation coefficient for these data?Why is this result reasonable?
Crime rate per 100,000 population Crime rate per 100,000 population Age in years Age in years 12 2,3332 34 5,851.8 13 3,918.8 35 5,716.1 14 6,846.2 36 5,522.7 15 10,008.6 37 5,641.7 16 12,755.9 38 5,582.5 17 14,814.1 39 5,366 2 18 14,406.7 40 5,523.5 19 13,833.7 41 4,950.4 20 12,533.1 42 5,315.9 21 12,120.1 43 5,089.3 22 11,180.2 44 4,533.3 23 10,649.1 45 4,5332 24 9,369.1 46 4,171.9 25 9,2422 47 3,990.9 26 8,798.2 48 3,862 2 27 7,856.6 49 3,336 2 28 7,625.7 50 3,130.5 29 7,277.1 51 3,000.4 30 6,999.7 52 2,485 2 31 6,638.1 53 2,494.8 32 6,715.1 54 2,173.5 33 6,030.9
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 Crash Fatality Rate 228 266 358 484 531 15.8 15.7 15.5 15.2 14.8 O A. Ho: pz0 H4:p= 0 O B. Ho: p=0 H1:p 0 H1: p#0 Construct a scatterplot. Choose the correct graph below. OA. YB. Oc. OD. Ay 17- Ay 17- Ay 17- Ay 17- 16- Q 16- 16- 16- 15- 15- 15- 15- X 14- 14- 14- 14+ 200 400 600 200 400 600 200 400 600 200 400 600 The linear correlation coefficient is r= - 0.971 (Round to three decimal places as needed.) The test statistic is t= (Round to three decimal places as needed.)
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…
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? 484 534 Lemon Imports Crash Fatality Rate 229 15.8 266 15.7 359 15.5 15.3 14.8 OC. Ho: p=0 H₁: p=0 Construct a scatterplot. Choose the correct graph below. O A. Ay 17+ 16- 15- 14- 0 200 400 600 Q Q The linear correlation coefficient is r= (Round to three decimal places as needed.) The test statistic is t- (Round to three decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value is OB. Ax 17+ 16- 15 14+ 6 than the significance level 0.05, there % 0 200 400 400 600 Q Q G OD. H₂:p#0 H₁:…
Listed below are the amounts of bills for dinner and the amounts of the tips that were left. 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=0.05. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) 33.75 52.16 86.46 91.98 62.80 95.27 Tip (dollars) 4.16 4.74 7.99 15.64 11.53 9.20 The linear correlation coefficient is r= (Round to three decimal places as needed.) Determine the null and alternative hypotheses. (Type integers or decimals. Do not round.) The test statistic is t= (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value of the linear correlation coefficient is ▼ greater than or…
Write a report using Word. Cover the following topics. This file contains some information about different cars. Car Weight (pounds), x Miles per Gallon, y A 2750 31.5 B 3120 27.9 C 3385 23.7 D 3740 23.3 E 4225 21 Create a scatterplot for the data in the Weight and Braking columns. Paste it here. a) Using StatCrunch or TI 83/84 to calculate the linear correlation between the data in the Weight and MPG columns. b) Explain the mathematical relationship between Weight and MPG based on the linear correlation coefficient. Be certain to include comments about the magnitude and the direction of the correlation. c) Write the equation for the least-squares regression line if there is one. d) Predict the miles per gallon of car C and compute the residual.
The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. 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. Should we expect that there would be a correlation? Use a significance level of a=0.05. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. A. 20- 20 E 70 OB. 70- 20+ 20 70 Best Actress (years) The linear correlation coefficient is r= (Round to three decimal places as nee Best Actress (years) Best Actresses and Best Actors Best Actress 28 31 30 64 31 Best Actor 44 39 37 43 49 33 46 47 56 OC. COD. Q 70- 20 20 Best Actress (years) 30 59 23 42 53 442 52 39 56 44 34 70 20 20 70 Best Actress (years)
The accompanying table lists the ages of acting award winners matched by the years in which the awards were won. 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. Should we expect that there would be a correlation? Use a significance level of a = 0.01. Click the icon to view the ages of the award winners. Construct a scatterplot. Choose the correct graph below. OA. 70- Best Actor (years) 20+ 20 Q [ 70 Best Actress (years) The linear correlation coefficient is r= ☐ (Round to three decimal places as needed.). B. OC. Q 70- 70- Q 20- 20 20- 70 20 70 Best Actress (years) Best Actress (years) Best Actresses and Best Actors Best Actress 29 29 28 57 31 32 45 28 63 22 42 51D Best Actor 45 39 39 47 51 49 64 48 38 55 43 34 O D. 70- Q G 20 20 70 Best Actress (years)
Listed below are amounts of bills for dinner and the amounts of the tips that were left. 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 = 0.05. If everyone were to tip with the same percentage, what should be the value of r? Bill (dollars) Tip (dollars) 69 Construct a scatterplot. Choose the correct graph below. O A. 25- 04 30 1.6 Bill Amount (S) 30.39 49.64 84.71 94.16 62.06 101.95 6.07 8.67 11.03 12.99 9.31 13.46 120 Q ✔ The linear correlation coefficient is r= (Round to three decimal places as needed.) Determine the null and alternative hypotheses. Ho: P H₁: p (Type integers or decimals. Do not round.) The test statistic is t = (Round to two decimal places as needed.) The P-value is (Round to three decimal places as needed.) Because the P-value of the linear correlation…