To examine the linear correlation between adult age and weight, data was collected from 9 adults. table below. Age Weight (Years) (pounds) 32 219 36 205 42 179 46 149 51 210 57 159 58 245 59 193 60 192 Does this result suggest that the correlation is statistically significant? Use a = 0.05. Important Note: Round your value for r to three decimals before computing the STS. DO NOT use the in LinRegTTest on a calculator because you might get marked wrong. When computing the P-value, u rounded STS. 1. Select the correct statement: O If the correlation is found to be statistically significant, that means that changes in x cause cha

To examine the linear correlation between adult age and weight, data was collected from 9 adults. table below. Age Weight (Years) (pounds) 32 219 36 205 42 179 46 149 51 210 57 159 58 245 59 193 60 192 Does this result suggest that the correlation is statistically significant? Use a = 0.05. Important Note: Round your value for r to three decimals before computing the STS. DO NOT use the in LinRegTTest on a calculator because you might get marked wrong. When computing the P-value, u rounded STS. 1. Select the correct statement: O If the correlation is found to be statistically significant, that means that changes in x cause cha

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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You wish to determine if there is a linear correlation between the age of a driver and the number of driver deaths. The following table represents the age of a driver and the number of driver deaths per 100,000. Use a significance level of 0.01 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 65 27 34 27 76 24 55 34 71 21 49 24 34 36 27 19 Ho: ρ = 0Ha: ρ ≠ 0 Find the Linear Correlation Coefficient r = Find the p-value p-value = The p-value is Less than (or equal to) αα Greater than αα The p-value leads to a decision to Reject Ho Accept Ho Do Not Reject Ho The conclusion is There is a significant positive linear correlation between driver age and number of driver deaths. There is a significant linear correlation between driver age and number of driver deaths. There is a significant negative linear correlation between driver age and number of driver deaths. There is insufficient evidence to make a…
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The maximum weights (in kilograms) for which one repetition of a half-squat can be performed and the jump heights (in centimeters) for 12 international soccer players are given in the accompanying table. The correlation coefficient, rounded to three decimal places, is r=0.692. At a =0.05, is there enough evidence to conclude that there is a significant linear correlation between the variables? E Click the icon to view the soccer player data. Determine the null and alternative hypotheses. Ho: p o Maximum Weights and Jump Heights Ha: p o Maximum Jump height, y Determine the critical value(s). weight, x 190 60 to = (Round to three decimal places as needed. Use a comma to separate answers as needed.) 185 56 155 55 Determine the standardized test statistic. 180 59 175 55 t= (Round to three decimal places as needed.) 170 65 What is the conclusion? 150 52 160 52 Ho. There V enough evidence at the 5% level of significance to conclude that there is a significant linear correlation between the…
Below is a list of vertical jumps (in cm) for 24 athletes who compete in various different sports.28 45 55 46 70 72 62 32 75 68 74 54 50 62 63 31 55 68 73 55 60 69 68 92Part A. Using # of classes = 4, create a frequency table for the given data set, and use your frequency table to construct a histogram.Part B. Using the data set above, calculate the quartiles Qi where i = 0, 1, 2, 3, 4, and construct a box-and-whiskers plot for this data set.Part C. Calculate the 15th percentile of this data set.
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