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%.
As you might be known that the opposite sides of a rectangle are equal.
so,
the perimeter of a rectangle becomes
length + breadth + length + breadth
2 length + 2 breadth
2 (length + breadth)
apply the terms,
2 (3x +5 + 3x^2+ 6x -10)
= 2 ( 3x^2 +9x -5)
= 6x^2 + 18x -10 units.
Answer:
x= -6
Step-by-step explanation:
equation: -10 - 2x = 2x + 14
subtract 14 from both sides: -24 - 2x = 2x
add 2x to both sides: -24 = 4x
divide both sides by 4: -6 = x
Answer:
The price would be 55.25 in U.S dollars, you saved 29.75. $85 x .35=29.75.
<span>7 less than the number t:
</span>7 < t
or
t > 7