MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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- Identify the type of correlation in the following scatter plot. e Skip step McCully, Aliyah 9. 24AMCCully21Carrow_forwardDetermine the type of direction of correlation that you would expect of the given case / situation. Speed of wind turbines and amount of electricity generated. no correlation positive correlation zero correlation negative correlationarrow_forwardPlease use the values from the given r values and assign the accurate value to the plots A,B,C, or D.arrow_forward
- Match the linear correlation coefficient to the scatter diagram. The scales on the x- and y-axes are the same for each diagram. (a) r= - (b) r= - 0.546 0.025 0.946 (c) r= - (d) r= - 1 Click the icon to view the scatter diagrams. ..... r= - 0.025 r= - 0.546 r= - 0.946 r= - 1 Drag each of the r-values given above into the appropriate area below. Explanatory Explanatory Explanatory Explanatory Response Response Response Response • .arrow_forwardPLEASE SHOW AN EXPLANATION FOR EACH PARTarrow_forwardA correlation of 0.5. The community of having a cat and dog average is 60% and SD = 15. find the score of people having cats that show 75%.arrow_forward
- Match the correlation coefficients with their scatterplots. Select the letter of the scatterplot below which corresponds to the correlation coefficient. (Click on image for a larger view.) B v 1. r = -0.74 с A ✓ 2. r = -0.49 3. r = -0.97 4. r = 0.76 A B Darrow_forwardWhich correlation would allows for the best prediction of Y based on X? Group of answer choices r = .50 r = .80 r = .05 r = -.90arrow_forwardUse the table to find the following, unit price being your (x) and units sold (y). a. Find linear correlation coefficient. Years of Experience Salary in 1000$ 2 3. 15 28 42 13 64 50 16 90 11 58 8 54 b. Find the line of best fit. c. How many units will sell if the unit price was 0.85.arrow_forward
- Let x be the average number of employees in a group health insurance plan, and let y be the average administrative cost as a percentage of claims. x 3 7 15 32 75 y 40 35 30 26 18 (a) Make a scatter diagram of the data and visualize the line you think best fits the data. Flash Player version 10 or higher is required for this question. You can get Flash Player free from Adobe's website. (b) Would you say the correlation is low, moderate, or strong? positive or negative? strong and negative moderate and negative strong and positive low and negative low and positive moderate and positive (c) Use a calculator to verify that Σx = 132, Σx2 = 6932, Σy = 149, Σy2 = 4725, and Σxy = 2997. Compute r. (Round your answer to three decimal places.)r = As x increases, does the value of r imply that y should tend to increase or decrease? Explain. Given our value of r, we cannot draw any conclusions for the behavior of y as x increases. Given our value of r, y should tend to…arrow_forwardUse a graphing calculator to create a scatter plot and find the line of best fit and the correlation coefficient for the following data. Round to the nearest hundredth. X 2 4 6 8124 10 Part: 0/2 y 2 3 6 7 10 15 19arrow_forwardUse the data in the table, which shows the average annual salaries (both in thousands of dollars) for public school principals and teachers in the U.S. for 11 years. Apply what you have learned in the previous tab to complete this graded lab questions. 1. Repeat the steps from tab #1 using this data to construct a scatter plot graph and calculate the correlation coefficient R. (Recall the corelation coefficient is R and not R Teachers y Principalsx 77.8 43.7 78.4 43.8 80.8 45.0 R= 80.5 45.6, 2. Does the R value represent a positive, negative or no correlation between the salaries ol the teachers and principals? As teacher salaries increase, what happens to prinicipal salaries? 10 11 81.5 45.9 84.8 48.2 12 13 87.7 49,3 3. Write the equation of the regression line for the data below. The equation is y= 14 91.6 51.3 52.9 Teachers y 15 16 95.7 54.4 COD 54.2 =D0.5873x-2.0s07o R=0.995, 17 95.7 4. Use the regression equation that you found in exercise #3 to predict the average annual salary…arrow_forward
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