The correlation matrix between the potential explanatory variables is given:1- 0,94 - 0,40 - 0,900,69- 0,9410,590,92 -0,56R= -0,400, 5910,35-0,49- 0, 350, 35- 0,56 - 0,49 - 0, 35-0,90 0,9210,691Determine the critical correlation coefficient based on the minimax rule.

The critical correlation coefficient based on the minimax rule can be determined by finding the…

Answered: The correlation matrix between the…

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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i need help explaining 3 out of the 6 correlations
The maximum weights (in kilograms) for which one repetition of a half squat can be performed and the times (in seconds) to run a 10-meter sprint for 12 international soccer players are shown in the attached data table with a sample correlation coefficient r of - 0.958. A 13th data point was added to the end of the data set for an international soccer player who can perform the half squat with a maximum of 210 kilograms and can sprint 10 meters in 1.99 seconds. Describe how this affects the correlation coefficient r. Use technology. Click the icon to view the data set. Data Table The new correlation coefficient r going from - 0.958 to (Round to three decimal places as needed.) Maximum weight, x Time, y 175 1.81 185 1.79 155 2.06 210 1.42 155 2.07 195 1.62 190 1.69 165 1.88 195 1.59 180 1.64 165 1.97 175 1.91 210 1.99
Select five pairs of variables from the table. For each pair, report the following items: Name of the variables Correlation coefficient of the variables Significance of the correlation coefficient Interpret the sign of the correlation coefficient Interpret the magnitude of the correlation coefficient Table 4: Correlations of Variables 1 2 3 4 5 6 7 8 9 10 Program 1 Effect. (127) Score Number .171* 1 of staff (125) (130) Public .338* .518*' 1 revenu (119) (123) (124) Private .311* .220* .431*' 1 revenue (120) (124) (122) (125) Comp. .451* .451*' .610*' .519*' Services (125) (128) (123) (125) Number .221* .947*' .504*' .242*' .457*' 1 of (125) (130) (123) (124) (128) (130) positions Board -.267 .026 -.044 -.095 -.186* .140…
What is the relationship between the attendance at a major league ball game and the total number of runs scored? Attendance figures (in thousands) and the runs scored for 9 randomly selected games are shown below. Attendance 24 54 59 17 32 58 30 26 18 Runs 5 14 14 5 7 8 10 6 4 Find the correlation coefficient: r=r= Round to 2 decimal places. The null and alternative hypotheses for correlation are:`H0: ` == 0`Ha:` ≠≠ 0 The p-value is: (Round to four decimal places) Use a level of significance of α=0.05α=0.05 to state the conclusion of the hypothesis test in the context of the study. There is statistically significant evidence to conclude that a game with higher attendance will have fewer runs scored than a game with lower attendance. There is statistically significant evidence to conclude that there is a correlation between the attendance of baseball games and the runs scored. Thus, the regression line is useful. There is statistically insignificant…
The maximum weights (in kilograms) for which one repetition of a half squat can be performed and the times (in seconds) to run a 10-meter sprint for 12 international soccer players are shown in the attached data table with a sample correlation coefficient r of -0.971. A 13th data point was added to the end of the data set for an international soccer player who can perform the half squat with a maximum of 210 kilograms and can sprint 10 meters in 2.01 seconds. Describe how this affects the correlation coefficient r. Use technology. Click the icon to view the data set. The new correlation coefficient r going from -0.971 to (Round to three decimal places a gets stronger, gets weaker, stays the same,

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The correlation matrix between the potential explanatory variables is given: 1 -0,94 -0,40 -0,90 0,69 1 -0,94 0,59 0,92 -0,56 1 0,35 -0,49 -0,90 0,92 0,35 1 -0, 35 0,69 -0,56 -0,49 -0,35 1 Determine the critical correlation coefficient based on the minimax rule. R=0,40 0,59