Given that the linear correlation coefficient $r$ between the explanatory variable $x$ and response variable $y$ is $r = 0.26$, we can determine the following:

The correlation coefficient $r$ represents the strength and direction of the linear relationship between two variables. In this case, $r = 0.26$ is a positive value, meaning there is a positive association between $x$ and $y$, even though it is relatively weak.

Since $r$ is positive, the slope of the regression line will also be positive, as the slope is directly proportional to $r$ in a simple linear regression context. Therefore, the correct answer is:

• Positive

Would you like more details on how the correlation coefficient affects the slope of the regression line, or do you have any further questions?

Here are some related questions for further exploration:

1. What does the value of the correlation coefficient imply about the strength of the relationship?
2. How does a stronger correlation coefficient (closer to 1 or -1) affect the slope?
3. Can the correlation coefficient determine causation between variables?
4. What would the slope be if the correlation coefficient were negative?
5. How is the slope of the regression line calculated from the correlation coefficient and standard deviations?

Tip: A correlation coefficient of 0.26 indicates a weak positive relationship, meaning the variables move in the same direction, but not very strongly.