Assume that you have paired values consisting of heights (in inches) and weights (in lb) from 40 randomly selected men. The li
1 answer:
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%.
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Answer:
Feed 1, Soybean meal required =
Feed 2, Corn meal required =
Step-by-step explanation:
Total feed is <em>1 ton</em> i.e. <em>2000 lbs</em>.
Let <em>x</em> be the amount of Feed 1 required.
Feed 1 has of protein.
Then, amount of Feed 2 required =
Feed 2 has of protein.
As per question, total protein required is of 2000 lbs
.
Adding (1) and (2) and putting it equal to total protein required.
Feed 1 required =
Feed 2 required =