Which of the following statements is correct?
1. The correlation always has the same units as the x variable but not the y variable.
2. The correlation always has the same units as the y variable but not the x variable.
3. A negative value for the correlation r indicates the data are strongly unassociated.
4. Changing the units of measurement of x or y does not change the value of the correlation r.

4. Changing the units of measurement of x or y does not change the value of the correlation r.

Correct a linear transformation for x and y as we can see in the formula defined for r, not affect the calculation of the correlation coefficient.

Step-by-step explanation:

Previous concepts

Pearson correlation coefficient(r), "measures a linear dependence between two variables (x and y). Its a parametric correlation test because it depends to the distribution of the data. And other assumption is that the variables x and y needs to follow a normal distribution".

In order to calculate the correlation coefficient we can use this formula:  

Solution to the problem

Let's analyze one by one the possible options:

1. The correlation always has the same units as the x variable but not the y variable.

False the correlation is an adimensional number without of units

2. The correlation always has the same units as the y variable but not the x variable.

False the correlation is an adimensional number without of units

3. A negative value for the correlation r indicates the data are strongly unassociated.

False when we got a negatie value for r means that we hae strong association but inversely proportional

4. Changing the units of measurement of x or y does not change the value of the correlation r.

Correct a linear transformation for x and y as we can see in the formula defined for r, not affect the calculation of the correlation coefficient.

please can you ask in English