Data was collected at a tennis court. It showed that being older implies that a player will stay for a shorter length of time. Whatis likely true?O There is no correlation between age and length of stay.O There is a correlation between age and length of stay. There may or may not be causation. Further studies would have to be done todetermine this.O There is a correlation between age and length of stay. However, there is no causation. This is because there is a decrease in the length ofstay with an increase in age.

Answered: Image /qna-images/answer/a6d46702-edb5-4a2c-ac02-ce950627567a.jpg

Answered: Data was collected at a tennis court.…

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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A graduate student is interested in how viewing different types of scenes affects working memory. For his study, he selects a random sample of 36 adults. The subjects complete a series of working memory tests before and after walking in an urban setting. Before the walk, the mean score on the test of working memory was 9.1. After the walk, the mean score was 1.4 higher. The graduate student has no presupposed assumptions about how viewing different types of scenes affects working memory, so he formulates the null and alternative hypotheses as: H00 : μDD = 0 H11 : μDD ≠ 0 Assume that the data satisfy all of the required assumptions for a repeated-measures t test. The graduate student calculates the following statistics for his hypothesis test: Mean difference (MDD) 1.4 Estimated population standard deviation of the differences (s) 1.6 Estimated standard error of the mean differences (sMDMD) 0.2667 Degrees of freedom (df) 35 The t statistic 5.25 The critical values of t…
There is a strong correlation between the number of students graduating from SVS and the population of squirrels in York Region. The most likely type of causal relationship is:A.cause and effect B.accidental C.presumed D.reverse cause and effect
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even though we may observe a strong relationship between the explanatory and response variables, a lurking variable may also influence the response vatiabke. This is reffered to as A. correlation B. confounding C.association D. causation
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Does "correlation imply causation"? Give one example in which a variable X ispositively correlated with another variable Y, but we cannot deduce that X causes Y.
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 0.05 and round all values to 4 decimal places. Driver Age Number of Driver Deaths per 100,000 65 26 33 25 38 34 42 30 17 34 80 20 30 35 71 29 65 28 50 30 Но: р %3D 0 На: р 2 0 Find the Linear Correlation Coefficient r = Find the p-value p-value The p-value is O Less than (or equal to) a O Greater than a The p-value leads to a decision to O Reject Ho О Аcсеpt Ho O Do Not Reject Ho The conclusion is There is a significant linear correlation between driver age and number of driver deaths. O There is insufficient evidence to make a conclusion about the linear correlation between driver age and number of driver deaths. O There is a significant negative linear correlation between driver age and number of driver deaths. O There is a significant positive…
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. Differentiate between correlation vs. causation. When two variables are correlated (such as strength and running speed), they are associated with one another. Explain how, even if there is a correlation between the two, one might not cause the other. Provide an example of an association between variables where a causal relationship makes sense conceptually. Why can't correlations be used as a tool to prove a causal relationship between variables rather than just an association?
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