Step-by-step explanation:
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56
Answer:
e= -5.41
Step-by-step explanation:
Hello!
In linear regression, a residual value is a distance between the observed values and the regression line.
The residual value (e) is calculated as the difference between the observed value (Y) and the predicted value (^Y).
e= Y - ^Y
e= 15.92 - 21.33 = -5.41
I hope it helps!
Answer:
y= -3 Your Welcome tell me if you got it right
Step-by-step explanation:
Answer:
3484m
Step-by-step explanation:
Add 1215(2) and 527(2) together
Answer:
The strongest relation between the two factors is B.) -0.8
Step-by-step explanation:
The correlation coefficient typically varies from -1 to 1.
The value of -1 for the correlation coefficient denotes that the two variables are have a very strong negative correlation.
The value of +1 for the correlation coefficient denotes that the two variables are have a very strong negative correlation.
Therefore among the four options given of -0.15, -0.8, 0.38, 0.03 the strongest relation between two factors is given by -0.8 but as the '-' sign indicates the two factors are negatively correlated.
Negative correlation means that if one variable is high the other would be low.
Positive correlation means that if one variable is high then the other variable is also high and if one variable is low then the other is also low.
