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 coefficientr, 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?228Lemon ImportsCrash Fatality Rate26635848453115.815.715.515.214.8O C. Ho: p=0YD. Ho: p=0H,:p>0H1: p#0Construct a scatterplot. Choose the correct graph below.O A.В.Oc.C.OD.Ay17-Ay174Ay17-Ay17-16-16-16-16-15-15-15-15-14-14-14+14-->600->200 400 600200400 600200400200400 600The linear correlation coefficient is r= -0.971.(Round to three decimal places as needed.)The test statistic is t= - 7.036.(Round to three decimal places as needed.)The P-value is(Round to three decimal places as needed.)

Fro t table we check the p-value at (n-1)= (5-1)= 4 d.f.

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 coefficie r, and find the P-value using ¤ = 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 15.8 266 15.7 358 15.5 484 15.2 531 14.8 O C. Họ: p=0 D. Họ: p=0 H;:p>0 H: pz0 Construct a scatterplot. Choose the correct graph below. O A. VB. Oc. OC. OD. AY 17- Q Q A> 171 17- 174 16- 16- 16- 16- 15- 15- 15- 15- 14+ 14- 200 400 600 14- 14- 200 400 60 200 400 600 200 400 600 The linear correlation coefficient is r= -0.971 (Round to three decimal places as needed.) The test statistic is t= -7.036. (Round to three decimal places as needed.) The P-value is N.

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 coefficie r, and find the P-value using ¤ = 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 15.8 266 15.7 358 15.5 484 15.2 531 14.8 O C. Họ: p=0 D. Họ: p=0 H;:p>0 H: pz0 Construct a scatterplot. Choose the correct graph below. O A. VB. Oc. OC. OD. AY 17- Q Q A> 171 17- 174 16- 16- 16- 16- 15- 15- 15- 15- 14+ 14- 200 400 600 14- 14- 200 400 60 200 400 600 200 400 600 The linear correlation coefficient is r= -0.971 (Round to three decimal places as needed.) The test statistic is t= -7.036. (Round to three decimal places as needed.) The P-value is N.

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? 484 534 Lemon Imports Crash Fatality Rate 229 15.8 266 15.7 359 15.5 15.3 14.8 What are the null and alternative hypotheses? OA. H₂: p=0 H₁: p0 OD. Ho: p*0 H₁: p=0 OC. Ay 17+ 16- ܕ 15 14+ HHHH ▬▬▬▬▬ % do 6 200 400 600 G O D. Aу 17- 16 :|||||||* 15- 14+ 0 H °. C M o do 200 400 600 Q C sufficient evidence to support the claim that there is a linear correlation between lemon imports and crash fatality rates for a significance level of a = 0.05.
Listed below are amounts of court income and salaries paid to the town justices. All amounts are in thousands of dollars. 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 court incomes and justice salaries? Based on the results, does it appear that justices might profit by levying larger fines? Court Income 65.0 406.0 1566.0 1130.0 273.0 251.0 112.0 152.0 32.0 Justice Salary 31 45 92 58 44 60 24 25 18 B. Ho:p=0 A. Ho:p=0 H4:p#0 H:p>0 O C. Ho: p=0 H4:p<0 O D. Ho: p+0 H1:p=0 Construct a scatterplot. Choose the correct graph below. O A. В. O D. AJustice Salary 100- AJustice Salary 100- A Justice Salary 100- AJustice Salary 100- 50- 50- 50- 50- 0- 0- 0- 800 1600 800 1600 800 1600 800 1600 Court Income Court Income Court Income Court Income The linear correlation coefficient is r= (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 α=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: 228 265 359 480 532 Crash Fatality Rates: 15.9 15.6 15.4 15.3 14.9 The linear correlation coefficient r is? The test statistic t is? The P-value is?
The trend of thinner beauty pageant winners has generated charges that the contest encourages unhealthy diet habits among young women. Listed below are body mass indexes (BMI) for beauty pageant winners from two different time periods. Find the coefficient of variation for each of the two sets of data, then compare the variation. The coefficient of variation for the BMI's of beauty pageant winners from the 1920s and 1930s is %
1945 is paired with cancer rates for 1975. The cigarette consumption data is from 1945 to 1975 in 5-year increments. There is a strong positive linear association between annual cigarette consumption and lung cancer rates. The correlation is 0.81. If we use the line to make predictions of the number of lung cancer deaths per 100,000 people, which of the following is an example of extrapolation? a. Predict Y when cigarette consumption is 3,500 cigarettes per person. b. Predict Y when cigarette consumption is 3,800 cigarettes per person. c. Predict Y when cigarette consumption is 4,600 cigarettes per person.
The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.692. At a =0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? E Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho: p o Maximum Weights and Jump Heights Ha: p o Maximum Jump height, y Determine the critical value(s). weight, x 190 60 to = (Round to three decimal places as needed. Use a comma to separate answers as needed.) 185 56 155 55 Determine the standardized test statistic. 180 59 175 55 t= (Round to three decimal places as needed.) 170 65 What is the conclusion? 150 52 160 52 Ho. There V enough evidence at the 5% level of significance to conclude that there is a significant linear correlation between the…
determine whether suicide and homicide rates in metropolitan areas around the country are correlated. a sample of 10 metropolitan areas with their rates (number per 100,000), of suicide and homicide. computed the correlation coefficient of 0.70.
Complete the following instructions:i. Identify the independent and dependent variables.ii. Calculate and interpret the Pearson correlation coefficient r for the paired data. Be sure to indicate if the correlation is positive or negative, and whether it is strong, moderate, or weak, or if there does not appear to be any significant correlation. A researcher for a gasoline retailer examines the relationship between the volume of gasoline purchased in kL(i.e. 1000 L) compared to the price of gasoline (in $/L), over a course of several days, to see if there is a correlation between the data: Amount of Gasoline Purchased Price of Gasoline 2.257 1.079 3.126 1.015 2.793 1.046 4.671 0.973 2.137 1.021 5.916 0.939 2.775 0.995 4.88 0.927 3.162 0.964 7.498 0.899 2.971 0.982 3.596 0.945 1.372 1.129 3.961 1.059 i. Independent Variable: Dependent Variable: ii. Pearson correlation coefficient (r): Round to 3 decimal…
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.)
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:…
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.
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