We assume data and prediction as question is incomplete
Answer and Step-by-step explanation:
Least squares regression line equations are used to model the relationship that exists between two variables, dependent and independent variables. The equation has the form y=a+bx where y is the dependent variable and x is independent variable, a is a constant and is the y intercept and b is the slope of the line. This relationship is then used to predict future outcomes.
Given that data for 2004-2005 for the basketball players are :
James- 20 points
John- 30 points
Chris- 50 points
Dave-15 points
Donaldson- 32 points
Richard -40 points
We predict the scores/points for James (for example) for the following year using the equation of the regression line y=0.79x+1544
We substitute his points x=20 I'm the equation:
Y=0.79*20+1544
=1599.8
The predicted value is 1599.8
Answer:
non - collinear points
Step-by-step explanation:
points that dont lie on the same line
Answer:
it increase by 31%
Step-by-step explanation:
1.31-1.00=.31 move the decimal place to the left 31%
