In a simple linear regression study between two variables x ( the independent variable) and y (the dependent variable), a random large sample is collected and the coefficient of correlation r = −.98 is calculated. Which of the following conclusion may be made? A.) x and y are almost perfectly correlated, and y increases as x is increased. B.) x and y are moderately correlated, and y increases as x is increased. C.) x and y are almost perfectly correlated, and y decreases as x is increased. D.) x and y are very poorly correlated since r close to -1.

C.) x and y are almost perfectly correlated, and y decreases as x is increased.

Step-by-step explanation:

The correlation r is a number between -1 and 1 and it shows the relation between variables x and y. If the number is closed to 0, there isn't a relation between x and y, however if the number is closed to -1 or 1 we can said that they are almost perfectly correlated.

Finally, if the number is positive, it means that y increases as x is increased. On the other side, if the number is negative, y decreases as x is increased.

In this case, r is -0.98, a number that is closed to -1 and negative, it means that x and y are almost perfectly correlated and y decreases as x is increased.

it is almost perfectly correlated. -.98, represents that it is 98% the same with a negative slope.

Step-by-step explanation:

< 6 cm to > 26 cm i believe

step-by-step explanation:

sine

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