Hi, I am working on linear regression and have a table that compares 8 high school girl's height in inches and IQ scores.
First I was to come up with an equation for this which I did, and it's y = .13x + 102.07.
The next question asks the slope, which I know is .13, but then it asks what that represents?
If x is height and y is IQ score, I know that it's comparing the 2, but I don't know what to say about it??
Last, it asks for the r value, the correlation coefficient. That value is 0.05, and then it asks for the meaning of the correlation coefficient. I'm not sure what to say there, either - is saying it's not close to 1 so therefore the data doesn't follow a pattern good enough?
Thank you
To understand what the slope represents in the equation y = 0.13x + 102.07, we need to consider the variables involved. In this case, x represents the height of high school girls in inches, and y represents their IQ scores. The slope, 0.13, indicates the rate of change in IQ score (y) for every one-unit change in height (x).
Specifically, for every one-inch increase in height, the IQ score is expected to increase by 0.13 points. This means that taller girls tend to have slightly higher IQ scores, according to this linear regression model.
Moving on to the correlation coefficient (r value) of 0.05, this measures the strength and direction of the linear relationship between height and IQ scores. However, a correlation coefficient of 0.05 suggests a weak and almost negligible correlation between the two variables. It indicates that there is very little linear association between height and IQ scores in the given dataset.
It's important to note that the closer the correlation coefficient is to 1 (either positive or negative), the stronger the linear relationship between the variables. Conversely, when the correlation coefficient is close to 0, as in this case, it suggests that there is minimal or no linear relationship between the variables.
Hence, the data in this specific context does not support a strong relationship or significant pattern between the height and IQ scores of the high school girls in the dataset.