900 divided by 15 will get you your answer which is....60:)
Answer:
The value of the coefficient of determination is 0.263 or 26.3%.
Step-by-step explanation:
<em>R</em>-squared is a statistical quantity that measures, just how near the values are to the fitted regression line. It is also known as the coefficient of determination.
A high R² value or an R² value approaching 1.0 would indicate a high degree of explanatory power.
The R-squared value is usually taken as “the percentage of dissimilarity in one variable explained by the other variable,” or “the percentage of dissimilarity shared between the two variables.”
The R² value is the square of the correlation coefficient.
The correlation coefficient between heights (in inches) and weights (in lb) of 40 randomly selected men is:
<em>r</em> = 0.513.
Compute the value of the coefficient of determination as follows:

Thus, the value of the coefficient of determination is 0.263 or 26.3%.
This implies that the percentage of variation in the variable height explained by the variable weight is 26.3%.
If there is a graph or something that you can show me, I'd be more than happy to help you.
1/8*3/4
multiply the numerators together
1*3=3
multiply the denominators together
8*4=32
answer:
3/32
The answer to this equation is 1/2