A measure of the strength of the relationship between two variables is referred to as the A. standard deviation of the estimate.
B. coefficient of determination. C. standard error of the estimate. D. coefficient of correlation.
1 answer:
Answer:
D. Coefficient of Correlation
Step-by-step explanation:
The name itself "Coefficient of Correlation" involves the word correlation, meaning relationship between two things.
The coefficient of Correlation is used to determine how strong a relationship is between two variables.
The formula of Coefficient of Correlation gives a value between -1 and 1. Moreover, it helps to plot a graph showing the strength of relationship.
1 : A strong positive relationship
-1: A Strong negative relationship
0: No relationship at all
One of the most used formula is Pearson Correlation Coefficient Formula, picture of which is attached. X and Y represent two different set of datas.
<u>Note: </u>
The other terms are defined as :
Coefficient of Determination : Square of correlation between predicted scores and actual scores. It usually ranges from 0 to 1 .
Standard deviation of estimate : represents the amount of variation among a set of values .
Standard Error of estimate : It is the measure of dispersion of sample means around population means.
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Answer:
x = or 0.706
or 1.735
Step-by-step explanation:
5x + 2y=7 ----->(eq 1)
- 2x + 6y=9 ----->(eq 2)
Multiply (eq 1) with 3
3×(5x + 2y) = 3×7
15x + 6y = 21 ----->(eq 3)
substract (eq 3) from (eq 2)
- 2x + 6y - (15x + 6y) = 9-21
- 2x + 6y - 15x - 6y = 9-21
- 2x - 15x + 6y - 6y = 9-21
-17x = -12
x = -12 ÷ -17
x =
put x = in (eq 1)