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%.
Answer:
3
Step-by-step explanation:
A difference of squares factors in general as
a² - b² = (a - b)(a + b)
Given the factor (- 5x + 3) of a difference of squares product.
Then the other factor is (- 5x + 3)
Answer:
a) y = x**2 - 3
Step-by-step explanation:
Let x = 0, then y = -3 or anything above (the unshaded area), so "a" fits.
No, it is not. If you plug 4 into the equation in the place of x, you get 13=2(4)+4
13=8+4
13=12
It equals 12, not 13.
Answer:
15 percent
Step-by-step explanation: You will substract the new value from the old value.
23-20
Now you will get the difference between them and divide that by the original amount.
3/20
This will equal 0.15 in which you now multiply by 100
15 percent