The ages (in years) of 10 men and their systolic blood pressures (in millimeters of mercury) are shown in the attached data table with a sample correlation coefficient r of 0.923. Removethe data entry for the man who is 51 years old and hasthis affects the correlation coefficient r. Use technology.systolic blood pressure of 198 millimeters of mercury from the data set and find the new correlation coefficient. Describe howE Click the icon to view the data set.The new correlation coefficient rgoing from 0.923 toData table(Round to three decimal places as needed.)Age, xSystolic bloodpressure, y16109261223714544131511986318571199301315817521119PrintDone

The independent variable is Age. The dependent variable is systolic blood pressure. We have to find…

Answered: The ages (in years) of 10 men and their…

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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Identify the type of correlation in the following scatter plot. e Skip step McCully, Aliyah 9. 24AMCCully21C
Use a graphing calculator to find the equation of the line of best fit for the data in the table below. Find the value of the correlation coefficient r. Then predict the number of movie tickets sold in 2014.
Please use the values from the given r values and assign the accurate value to the plots A,B,C, or D.
Identify the correct statement below: a. The correlation between eye colour and salary is positive b. The correlation between shoe size and eye color is 0.45. c. The correlation between the weight of a mother and the weight of her daughter is 0.8 d. The correlation between height and weight is 2.5.
Which correlation would allows for the best prediction of Y based on X? Group of answer choices r = .50 r = .80 r = .05 r = -.90
Suppose that the correlation between height and IQ in children is +0.70. What proportion (or percent) of the variability in IQ can be explained by the relationship with height? Select one: a. 44% b. 51% c. 70% d. 49%
The correlation between midterm and final grades for 300 students is 0.620. If 5 points are added to each midterm grade, the new r will be: a. 0.124 b. 0.57 c. 0.62 d. 0.744
Given the scatter plot shown, determine if the correlation is positive, negative, or if there is no relative correlation. Correlation for this scatter plot: Select an answer
Suppose the correlation between height and weight for adults is +0.80. What proportion of the variability in weight can be explained by the relationship with height? A. 20% B. 36% C. 64% D. 80%
Based on the given scatter diagram, choose the correct statement. a. It is a positive correlation. The more time an individual spends running, the higher their body fat tends to be. b. It is a positive correlation. The more time an individual spends running, the lower their body fat tends to be. c. It is a negative correlation. The more time an individual spends running, the higher their body fat tends to be. d. It is a no correlation. The amount of time an individual spends running has no correlation with his/her body fat tends to be. e. It is a negative correlation. The more time an individual spends running, the lower their body fat tends to be.
Use 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 19
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.

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