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 usinga = 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?65.0 403.0 1568.01132.0 271.0 252.0 112.0 150.0 34.0 e3142Court IncomeJustice Salary91 574660242517What are the null and alternative hypotheses?B. Ho: p=0O A. Ho: p=0H1:p>0H1:p#0O C. Ho: p=0O D. Ho: pz0H,:p<0H,:p=0Construct a scatterplot. Choose the correct graph below.O A.OB.OC.OD.O D.AJustice Salary100-AJustice Salary100-AJustice Salary100-AJustice Salary100-50-50-50-5어 ..0-0-0-0-8001600800160080080016001600Court IncomeCourt IncomeCourt IncomeCourt Income

Provided information is ; level of significance(α)=0.05 data is ; Court income(x) 65 403 1568…

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 | 403.0|1568.0|1132.0 271.0| 252.0|112.0| 150.0| 34.0 |e Justice Salary 31| 42 | 91 57 | 46 60 24 25 17 What are the null and alternative hypotheses? B. Hg: p=0 O A. Ho: p=0 H:p>0 OC. Ho: p=0 O D. Ho: p#0 H,:p=0 H,:p<0 Construct a scatterplot. Choose the correct graph below. OA. O B. Oc. OD. AJustice Salary 100- AJustice Salary 100- AJustice Salary 100- AJustice Salary 100- Q 50- 50- ...-- 50- 50- 0- 0- 0++ 0++ 1600 800 Court Income 800 1600 Court Income 800 1600 800 1600 Court Income Court Income

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 | 403.0|1568.0|1132.0 271.0| 252.0|112.0| 150.0| 34.0 |e Justice Salary 31| 42 | 91 57 | 46 60 24 25 17 What are the null and alternative hypotheses? B. Hg: p=0 O A. Ho: p=0 H:p>0 OC. Ho: p=0 O D. Ho: p#0 H,:p=0 H,:p<0 Construct a scatterplot. Choose the correct graph below. OA. O B. Oc. OD. AJustice Salary 100- AJustice Salary 100- AJustice Salary 100- AJustice Salary 100- Q 50- 50- ...-- 50- 50- 0- 0- 0++ 0++ 1600 800 Court Income 800 1600 Court Income 800 1600 800 1600 Court Income Court Income

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 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. Use a significance level of a = 0.01. Click to view the data on shoe print lengths and heights. Construct a scatterplot. Choose the correct graf Shoe Print Lengths versus Heights of Males O B. OD. 210- 200- 190- 180- 170- 160- 20 24 28 32 36 40 Shoe Print Length (cm) 210 200 190 180 170 160 2101 200- Shoe Print 190- Length (cm) Height (cm) 176.0 180- 170- 160- 20 24 28 32 36 40 31.4 28.9 181.2 31.5 194.5 Shoe Print Length (cm) 32.3 172.9 30.4 174.0 The linear correlation coefficient is r= 32.9 190.5 (Round to three decimal places as needed.) 31.0 176.6 30.8 170.0 30.5 171.9 32.3 175.5 30.5 200.1 32.6 199.3…
Which correlation coefficient indicates that you have the strongest connection between the variables in the data? O r= 0.88 O r= -0.89 O r= 0.93 O r= -0.95 ent.mastensonnect.com/ Ipe bese to search
The table lists weights (pounds) and highway mileage amounts (mpg) for seven automobiles. Use the sample data to construct a scatterplot Use the first variable for the x-axis. Based on the scatterplot, what do you conclude about a linear correlation? 2425 Weight (Ib) Highway (mpg) 2725 2875 3480 4070 4090 3125 34 33 30 25 24 36 31 Which scatterplot below shows the data? O A. OB. C. O D. 40- 40- 40 20+ 2000 20- 2000 Weight (Ib) 20어 2000 20- 2000 Weight (Ib) 5000 5000 5000 5000 Weight (Ib) Weight (Ib) Is there a linear relationship between weight and highway mileage? O A. No, there appears to be no relationship. O B. Yes, as the weight increases the highway mileage increases. O C. No, there appears to be a relationship, but it is not linear. Click to select your answer. 4:21 PM a 17 梦 * v 6/4/2021 W 0 門 e Type here to search Chp ins prt sc delet fg ho ト f8 144 f6 10 f5 f4 IOI esc back & #3 $4 4 T. 6, 00 %24 (6 d) AamH 3. (B dw) Am
Jim and Larry run a soup stand. The data below represents the sales of soup that they had on 8 randomly selected days, along with the high temperature on that day. a) Create a scatter diagram for this data set and comment on whether there is a positive or negative relationship between these variables.b) Calculate the correlation coefficient between temperature and sales.c) Does a linear relationship exist between these variables? Explain to me why or why not this is the case.d) Using excel, calculate the least squares regression equation for this data set. e) Using your equation, predict the soup sales on a day where the temperature is 29 degrees.f) Interpret the slope of this equation.g) Can we use this data set and regression equation to predict the sales on a day when the average temperature is 102 degrees? Why or why not?h) What is the R-squared for this equation? How do you interpret that R-squared?
Click this Video for Finding Correlation Coefficient by Using Formula. Yessica thought that there was a correlation between the amount of time students slept the evening before their final exam and their final exam grade. She took an SRS of 5 students in her class and recorded the sleep time the evening before their final exam, and their final exam score. Let the sleep time the evening before the final exam represents the explanatory variable, and the final exam score be the response variable. Below is a sample data set. x (hour) 8 9 3 9 1 2 3 4 5 Calculate the sample correlation coefficient (r) to three decimal places. r= 9 Why would we expect the correlation coefficient to be positive? As the sleep time increases, exam score increases As the sleep time increases, exam score decreases As the sleep time decreases, exam score increases There is no change in exam score to sleep time C E y (score) 91 94 51 100 90 C A
2. State whether the variables described have a positive correlation, a negative correlation, or no correlation. (a) Income and SAT scores (b) Length of a person's hair and how far they sit from the screen in a movie theater. (c) Hours of exercise per week and blood pressure.
An economist wants to determine whether there is a linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. The data are shown in the table below. c. Compute and interpret the correlation coefficient. d. Compute and interpret the coefficient of determination. e. Test for the significance of the linear relationship. Use a 0.05 level of significance. State your conclusion. Hint: Your conclusion is either of the following. • There is a significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. • There is no significant linear relationship between a country's gross domestic product (GDP) and carbon dioxide emissions. GDP 1.6 3.6 4.9 1.1 0.9 2.9 2.7 2.3 1.6 1.5 (trillion dollars) Carbon Dioxide Emissions 428.2 828.8 1214.2 444.6 264 415.3 571.8 454.9 358.7 573.5 (millions of metric tons)
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 %#3
The data below are the ages and annual pharmacy b ills (in dollars) of 9 randomly selected employees. Calculate the linear correlation coefficient.Age, x: 30, 33, 37, 40, 43, 45, 49, 53, 57Pharmacy bill ($), y: 119, 123, 126, 134, 145, 148, 151, 153, 155A. 0.890B. 0.908C. 0.998D. 0.960
A manager wishes to determine the relationship between the number of years the manager's sales representatives have been with the company and their average monthly sales (in thousands of dollars). Calculate the linear correlation coefficient.Years with company, x: 6,7,14,11,12,19,7,5,15Sales, y: 21,23,68,52,55,51,38,45,110
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 Justice Salary 65.0 406.0 1566.0 1131.0 274.0 253.0 110.0 152.0 31.0 e 29 45 94 58 46 61 25 26 19 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.) V than the significance level 0.05, there court incomes and justice salaries for a significance level of a = 0.05. Because the P-value is V sufficient evidence to support the claim that there is a linear correlation between Based…
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