Here is data comparing the vehicle engine size in liters to city mile per gallon (mpg). Size 6.2 5.4 3.0 3.7 3.6 5.0 6.4 3.5 City 13 16 20 19 19 17 15 17 mpg Graph the scatter plot. Is the data approximately linear? [Select ] Test the claim of correlation at the a = 0.5level of significance. Find the P-value [ Select ] Will the null hypothesis be rejected? [Select ] Round the regression equation to nearest integer and use it to predict the city mpg of a vehicle with an engine 4.5 Lin size. [ Select ]

Here is data comparing the vehicle engine size in liters to city mile per gallon (mpg). Size 6.2 5.4 3.0 3.7 3.6 5.0 6.4 3.5 City 13 16 20 19 19 17 15 17 mpg Graph the scatter plot. Is the data approximately linear? [Select ] Test the claim of correlation at the a = 0.5level of significance. Find the P-value [ Select ] Will the null hypothesis be rejected? [Select ] Round the regression equation to nearest integer and use it to predict the city mpg of a vehicle with an engine 4.5 Lin size. [ Select ]

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

See similar textbooks

Similar questions

The data below was collected from manufacturer advertisements of their vehicles horsepower (x) and highway gas mileage (mpg=y). Use this data to answer the following questions. horsepower 146 250 340 350 390 190 220 mpg 33 28 15 17 11 35 42 1. Find the p-value to determine if there is a linear correlation between horsepower and highway gas mileage (mpg). Record the p-value below. Round to four decimal places.p-value==2. Is there a linear correlation between horsepower and highway gas mileage (mpg)? 3. If there is a linear correlation, write the correlation coefficient below. Otherwise, leave it blank. Round your final answer to four decimal places. Be careful with your sign.r=r= 4. If there is a linear correlation, write the regression equation below. Otherwise, leave it blank. Round all numbers to four decimal places.ˆy=y^=5. Using the data shown above, predict the the highway gas mileage (mpg) for a car that has a horsepower of 225. Round your final answer to two decimal…
The authors of a paper presented a correlation analysis to investigate the relationship between maximal lactate level x and muscular endurance y. The accompanying data was read from a plot in the paper. X 390 740 760 y 3.90 r 3.90 5.00 5.30 4.10 3.60 6.20 OH₂: P = 0 Ha: P 0 1,465 1,470 1,495 2,190 t = P-value = 6.98 7.45 4.85 7.70 4.55 6.70 8.80 OH₂: P = 0 H₂: P = 0 Compute the value of the sample correlation coefficient, r. (Round your answer to four decimal places.) Calculate the test statistic and determine the P-value. (Round your test statistic to one decimal place and your P-value to three decimal places.) State the conclusion in the problem context. O Fail to reject Ho. A positive correlation exists between maximum lactate level and muscular endurance. Reject Ho. A positive correlation exists between maximum lactate level and muscular endurance. O Fail to reject Ho. A positive correlation does not exist between maximum lactate level and muscular endurance. O Reject Ho. A…
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)
Perform rank correlation analysis on the following data set: x y -5 1.9 -4 0.9 -3.25 0.7 -2.55 -0.5 -1.85 -1.2 -0.9 -1.7 5.5511151231258E-17 0.7 0.8 1.5 1.55 1.6 2.35 -0.1 3.3 0.8 4.1 -1.1 5.1 -0.9 5.8 -0.8 6.7 0.7 What is the rank correlation coefficient? (Round to three decimal places.) What is the critical rho value at a 0.01 significance? Do we have correlation? Yes, the rank correlation coefficient is smaller (in absolute value) than the critical rho value. No, the rank correlation coefficient is larger (in absolute value) than the critical rho value. No, the rank correlation coefficient is smaller (in absolute value) than the critical rho value. Yes, the rank correlation coefficient is larger (in absolute value) than the critical rho value.
The numbers of pass attempts and passing yards for seven professional quarterback for a recent year are listed in the table below. Round all answers to the nearest 1000th. Pass attempts (x) 449 565 528 197 670 351 218 Passing Yards (y) 3265 4018 3669 1141 5177 2362 1737 Calculate the sample correlation coefficient, r. Describe the type of correlation coefficient and interpret the correlation in the context of the data. Find the equation of the regression line for the data. Use the regression equation to predict the average number passing yards if the pass attempts are 250.
The data below is 12 observations of Math SAT scores (x) and scores on Math placement test (y). Calculate the linear correlation coefficient, rr. Enter your answers to two decimal places. X Y 420 426 410 360 600 575 460 538 550 553 480 407 560 635 450 388 400 383 430 402 470 462 440 437 rr =
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…
For a data set of brain volumes (cm3) and IQ scores of six males, the linear correlation coefficient is r=0.647. Use the table available below to find the critical values of r. Based on a comparison of the linear correlation coefficient r and the criticalvalues, what do you conclude about a linear correlation? LOADING... Click the icon to view the table of critical values of r. The critical values are nothing
Listed below are paired data consisting of amounts spent on advertising (in millions of dollars) and the profits (in millions of dollars). Determine if there is a significant linear correlation between advertising cost and profit Use a significance level of 0.01 and round all values to 4 decimal places. Advertising Cost Profit 3 21 4 16 5 29 17 7 28 8 21 Ho: p = 0 Ha: p +0 Find the Linear Correlation Coefficient r= Find the p-value p-value = The p-value is Less than (or equal to) a OGreater than a The p-value leads to a decision to Do Not Reject Ho OReject Ho OAccept Ho
The data shows a systolic and a diastolic blood pressure of certain patients. Find the linear regression eqation, using the first variable (systolic) as the independent variable. Find the best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140. Use a significance level of x Systolic Diastolic 116 82 124 88 112 72 144 95 138 96 112 76 145 88 124 76 130 90 129 94 1)Find the correlation coefficient. 2)State the appropriate critical r value to use to test the claim that the correlation between systolic blood pressure and diastolic blood pressure is significantly different from 0 3)The correlation between diastolic blood pressure and systolic blood pressure is: significant, not significant, weak, none 4)The best predicted diastolic blood pressure for a patient with a systolic blood pressure reading of 140 is closest to 1pts
The paired data below consists of heights and weights of 6 randomly selected adults. Find the linear correlation coefficient, the linear regression line, and predict the weight of a randomly selected person who is 1.69 meters tall. X Height (meters) 1.61 1.72 1.78 1.80 1.67 1.88 Y Weight (kg) 54 62 70 84 61 92
Based on the scatter plot below on data from Central Harlem, would you estimate the correlation coefficient to be positive, negative, or close to 0? Select the correct correlation and corresponding explanation. Household Income vs. Serious Crime Rate (per 1,000 residents) CentralHarlem Data Scatter Plot: 22- 21- 20- 19- 18- 17 16- 15 32 34 36 38 40 42 Household_Income (thousands) Positive; As the household income increases, the serious crime rate decreases. A. Negative; As the household income increases, the serious crime rate decreases. B. Positive; As the household income increases, the serious crime rate also increases. OC. Negative; As the household income increases, the serious crime rate also increases. D. Close to 0; There is no linear correlation between household income and serious crime rate. E. A Moving to another question will save this response. Question 24 of 25 MacBook Air Serious crime_rate