A student of Engineering conducted a research to determine the correlation betweenperformance of 2 lathes in the workshop. Assessments were conducted on weekly basis, and thefollowing data were obtained. Calculate the coefficient of correlation using Karl Pearson'smethod, and discuss the level of the relationship.Table 2. The performance of the lathes on weekly basis.Week(s)1st2nd3rd4th5th6th7th8th9th10thLathe A42484028469028561622Lathe B56787224604236822834良

Given that Let X denotes performance of Lathe A and Y denotes the performance of Lathe B We have…

Answered: A student of Engineering conducted a…

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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Use the data to the right to complete parts (a) through (d) below. Percentage Who Won't Try Don't Approve of Sushi Marriage Equality Generation Millennials y 32 39 Gen X Boomers Silent/Greatest Generation 54 52 61 55 69 66 a. Determine the correlation coefficient between the percentage of people who won't try sushi and the percentage who do not approve of marriage equality. (Do not round until the final answer. Then round to two decimal places as needed.) b. What explanations can you offer for the correlation coefficient in part (a)? Choose the correct answer below. O A. Unwillingness to try sushi and disapproval of marriage equality have a weak positive correlation. O B. Unwillingness to try sushi and disapproval of marriage equality have a strong negative correlation. C. Unwillingness to try sushi and disapproval of marriage equality have no correlation. O D. Unwillingness to try sushi and disapproval of marriage equality have a strong positive correlation. c. Find the equation of…
A survey was taken in 2018 that asked people about their saving habits. Researchers wanted to know if people who saved more also spent less. The scatterplot below shows their results when comparing two variables: the amount people reported that they put into savings each month, and the amount they reported that they spent on clothes. The researchers found the correlation coefficient for this data to be -0.239. Which of the following is true about these variables? a. There is no relationship between savings and money spent on clothes each month.b. There is a weak, positive linear relationship between savings and money spent on clothes each month.c. There is a perfect, negative linear relationship between savings and money spent on clothes each month.d. There is a weak, negative linear relationship between savings and money spent on clothes each month.
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 following statement contains an error. Choose the statement that best explains the error. "The correlation between shoe size and height is 0.87 inches" A. Correlation requires that both of the variables be categorical B. When stating the correlation coefficient, one must state whether it is a positive or negative relationship C. This statement does not tell us whether or not shoe size is correlated with height D. When reporting correlation, one does not report units because correlation has no units E. There is no error in this statement
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…
If the linear association between two numerical variables is studied and the correlation coefficient is 0.32, it can be concluded that:a. The relationship between the variables is inverse and weak. b. The percentage of variability observed in the data that is explained by the error is 89.76%. c. The percentage of observed variability in the data that is explained by the model is 32%. d. None is correct Please explain clearly, thank you
A random sample of college students was surveyed about how they spend their time each week. The scatterplot below displays the relationship between the number of hours each student typically works per week at a part- or full-time job and the number of hours of television each student typically watches per week. The correlation between these variables is r = –0.63, and the equation we would use to predict hours spent watching TV based on hours spent working is as follows: Predicted hours spent watching TV = 17.21 – 0.23(hours spent working) Since we are using hours spent working to help us predict hours spent watching TV, we’d call hours spent working a(n) __________________ variable and hours spent watching TV a(n) __________________ variable. The correlation coefficient, along with what we see in the scatterplot, tells us that the relationship between the variables has a direction that is _________________ and a strength that is ______________________. According to the…
Assume that you have paired values consisting of heights (in inches) and weights (in lb) from 40 randomly selected men. The linear correlation coefficient r is 0.594. Find the value of the coefficient of determination. What practical information does the coefficient of determination provide? Choose the correct answer below. O A. The coefficient of determination is 0.353. 64.7% of the variation is explained by the linear correlation, and 35.3% is explained by other factors. O B. The coefficient of determination is 0.647. 35.3% of the variation is explained by the linear correlation, and 64.7% is explained by other factors. O C. The coefficient of determination is 0.647. 64.7% of the variation is explained by the linear correlation, and 35.3% is explained by other factors. O D. The coefficient of determination is 0.353. 35.3% of the variation is explained by the linear correlation, and 64.7% is explained by other factors.
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
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.
Suppose we measure the heights (in inches) and weights (in pounds) of 100 randomly chosen college students. Furthermore suppose we calculate the correlation to be 0.6. If we change the measurements to centimeters and kilograms, what happens to the value of the correlation? Note: There are 2.54 centimeters in an inch, and there are 2.2 pounds in a kilogram. Group of answer choices: A. The correlation increases by a factor of 2.54/2.2 B. The correlation is still 0.6. C. The correlation decreases by a factor of 2.2. D. The correlation increases by a factor of 2.54.
A graduate teaching assistant for an Introduction to Statistics course collected data from one of her classes to investigate the relationship between using the explanatory variable x=study time per week (average number of hours) to predict the response variable y=college GPA. For the 21 females in her class, the correlation was 0.42. For the eight males in her class, the data were as shown in the following table. Complete parts a through c below. Student 1 2 3 4 5 6 7 8 Study Time 15 6 22 13 24 4 10 15 GPA 3.4 2.8 3.9 3.2 3.7 2.7 3.2 2.7 a. Construct a scatterplot. Interpret. Which scatterplot below correctly shows the data? A. 04004xy A scatterplot has a horizontal x-axis labeled from 0 to 40 in increments of 10 and a vertical y-axis labeled from 0 to 4 in increments of 1. A cluster of plotted points that form a line that rises from left to right lie between…

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