Test 2: Correlation. Given the following data of 26 observations:XYXY165130172153167133159128180150168132155128174149212151183158175146215150190150195163210140180156200148143124149125240170158133235165169135192160170150187159Assume that X and Y are jointly normally distributed.A. Fit a regression line relating both variables. Create a scatter plot and add the regression line. Label theplots properly. Include the equation of the trendline and the value of R² (no need to show the solution forR²).B. Compute the sample correlation coefficient between the two variables. Show your solution.C. Construct a 95% confidence interval on p.D. Test the hypothesis that Pxy #0 at the 0.05 level of significance.

Given that, X and Y are jointly normally distributed.

Answered: Assume that X and Y are jointly…

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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An HP laser printer is advertised to print text documents at a speed of 18 ppm (pages per minute). The manufacturer tells you that the printing speed is actually a Normal random variable with a mean of 17.57 ppm and a standard deviation of 3 ppm. Suppose that you draw a random sample of 11 printers. Part i) Suppose the number of printers drawn is quadrupled. How will the standard deviation of sample mean printing speed change? O A. It will decrease by a factor of 4. OB. It will increase by a factor of 4. O C. It will increase by a factor of 2. O D. It will decrease by a factor of 2. OE. It will remain unchanged. Part ii) Suppose the number of printers drawn is quadrupled. How will the mean of the sample mean printing speed change? O A. It will decrease by a factor of 2. O B. It will decrease by a factor of 4 O C. It will increase by a factor of 4. O D. It will increase by a factor of 2. OE. It will remain unchanged. Part iii) Consider the statement: 'The distribution of the mean…
A researcher would like to predict the dependent variable Y from the two independent variables X1 and X2 for a sample of N = 15 subjects. Use multiple linear regression to calculate the coefficient of multiple determination and test the significance of the overall regression model. Use a significance level a = 0.01. X1 X2 Y 38.4 58.8 48.2 63.4 47.9 55.6 48.4 54.6 33.1 54.9 48.7 47.4 54.8 54.2 51.7 44.1 78.6 64.8 55.3 48 38.6 56.8 54.3 34.1 56.5 61 42.6 52.1 49.2 35.8 57.5 49.4 51.2 55.3 66.7 56.7 57.5 53.5 25.6 71.8 64.4 63.3 29.1 62.8 56.7 Sreg SS.res R F P-value =
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 11 9 12 8 11 13 4 13 6. 6 У 7.25 7 12.94 7.22 8.15 9.27 6.33 5.3 8.52 6.14 5.46 Create a scatterplot of the data. Choose the correct graph below. O B. OC. O D. O A. Ay 25- Ay 25- 25- 25- 20- 20 20- 20 15 15 15 15 10 10 10- 10 5- 5- 5- 5- 0- 05 10 15 20 25 05 10 15 20 25 0- 05 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. O A. There is no trend in the data. O B. The data has a pattern that is not a straight line. C. There is an influential point that strongly affects the graph of the regression line. D. There is no characteristic of the data that is ignored by the regression line. Click to select your answer(s).…
Use the given data to find the equation of the regression line. Examine the scatterplot and identify a characteristic of the data that is ignored by the regression line. 9 9 11 10 11 14 4 13 7 6 y 7.59 6.87 13.06 7.32 8.58 6.09 5.62 8.35 6.73 7.77 5.9 Create a scatterplot of the data. Choose the correct graph below. O A. OB. OC. Oc. OD. Ay 25- Ay 25- Ay 25- 25- 20 20- 20- 20- 155 155 155 155 105 105 105 105 5- 55 55 55 0- Ó 5 10 15 20 25 0- 0- 05 10 15 20 25 Ó 5 10 15 20 25 0 5 10 15 20 25 Find the equation of the regression line. (Round the constant two decimal places as needed. Round the coefficient to three decimal places as needed.) Identify a characteristic of the data that is ignored by the regression line. O A. The data has a pattern that is not a straight line. O B. There is no characteristic of the data that is ignored by the regression line. OC. There is an influential point that strongly affects the graph of the regression line. O D. There is no trend in the data.
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The data show the chest size and weight of several bears. Find the regression equation, letting chest size be the independent (x) variable. Then find the best predicted weight of a bear with a chest size of 40 inches. Is the result close to the actual weight of 392 pounds? Use a significance level of 0.05. Chest size (inches) Weight (pounds) E Click the icon to view the critical values of the Pearson correlation coefficient r. 41 54 44 55 39 51 328 528 418 580 296 503 ..... What is the regression equation? y =+x (Round to one decimal place as needed.) What is the best predicted weight of a bear with a chest size of 40 inches? The best predicted weight for a bear with a chest size of 40 inches is pounds. (Round to one decimal place as needed.) Is the result close to the actual weight of 392 pounds? O A. This result is close to the actual weight of the bear. O B. This result is exactly the same as the actual weight of the bear. O C. This result is very close to the actual weight of the…
6. Which of the following are true? Select all that apply. a. The coefficient of determination is the proportion of variation in the response variable that is explained by the regression line. b. We often use the symbol r to represent the coefficient of determination. c. In simple linear regression, the coefficient of determination equals the square of the linear correlation coefficient r. d. The closer the regression line comes to the data points, r should go to eleven.
Suppose that you want to compare the means of several treatments in a randomized block ANOVA. If given the choice between using the randomized block ANOVA test and the Friedman test, which one would you choose if outliers occur in the sample data? Explain your answer.
Run a regression analysis on the following bivariate set of data with y as the response variable. y 56.3 -257.6 14.5 670.8 49.4 431 60.7 200.3 60.1 70.3 52.6 -162.4 46.2 -406.9 45.1 -3.6 39.6 292.4 51.2 274.8 53.1 -77.4 50 496.6 46.9 251.5 48.5 -188.7 79.8 233 33.5 -415.6 49.2 431.3 download link provided here: Download CSV Predict what value (on average) for the response variable will be obtained from a value of 32.1 as the explanatory variable. Use a significance level of a = 0.05 to assess the strength of the linear correlation. What is the predicted response value? y = 169.94127 (Report answer accurate to one decimal place.)

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