For a data set of brain volumes (cm³) and IQ scores of four males, the linear correlation coefficient isr= 0.979. Usethe table available below to find the critical values of r. Based on a comparison of the linear correlation coefficient r andthe critical values, what do you conclude about a linear correlation?Click the icon to view the table of critical values of r.The critical values are(Type integers or decimals. Do not round. Use a comma to separate answers as needed.)Table of Critical Values of rNumber of Pairsof Data nCritical Value of r4.0.9500.8780.8110.75480.7070.666100.632110.602120.576PrintDone

Critical value method is one of the two ways of testing null hypothesis.

Answered: For a data set of brain volumes (cm)…

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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For a data set of chest sizes (distance around chest in inches) and weights (pounds) of ten anesthetized bears that were measured, the linear correlation coefficient is r=0.906. Use the table available below to find the critical values of r. Based on a comparison of the linear correlation coefficientr and the critical values, what do you conclude about a linear correlation? Click the icon to view the table of critical values of r. The cnitical values are (Type integers or decimals. Do not round. Use a comma to separate answers as needed.) it:
Customers at a large department store rated their satisfaction with their purchases, on a scale from 1 (least satisfied) to 10 (most satisfied). The cost of their purchases was also recorded. To three decimal places, determine the correlation coefficient between rating and purchase amount spent. Then describe the strength and direction of the relationship.
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
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…
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
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…
The trend of thinner beauty pageant winners has generated charges that the contest encourages unhealthy diet habits among young women. Listed below are body mass indexes (BMI) for beauty pageant winners from two different time periods. Find the coefficient of variation for each of the two sets of data, then compare the variation. The coefficient of variation for the BMI's of beauty pageant winners from the 1920s and 1930s is %
For a sample of eight bears, researchers measured the distances around the bears' chests and weighed the bears. Minitab was used to find that the value of the linear correlation coefficient is r = 0.862. Using a = 0.05, determine if there is a linear correlation between chest size and weight. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? Click here to view a table of critical values for the correlation coefficient. a. Is there a linear correlation between chest size and weight? O A. No, because the absolute value of r exceeds the critical value of 0.707. O B. Yes, because r falls between the critical values of -0.707 and 0.707. O C. Yes, because the absolute value of r exceeds the critical value of 0.707. O D. The answer cannot be determined from the given information. b. What proportion of the variation in weight can be explained by the linear relationship between weight and chest size? (Round to three decimal…
For a data set of chest sizes (distance around chest in inches) and weights (pounds) of twelve anesthetized bears that were measured, the linear correlation coefficient is r= 0.276. Use the table available below to find the critical values of r. Based on a comparison of the linear correlation coefficient r and the critical values, what do you conclude about a linear correlation? Click the icon to view the table of critical values of r. The critical values are Table of Critical Values of r IT Number of Pairs of Data n Critical Value of r 4 0.950 0.878 0.811 7 0.754 0.707 0.666 10 0.632 11 0.602 12 0.576
Here is a scatterplot. Give an estimate for the correlation coefficient r and explain how you made your choice.
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
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

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