Answer:
Squared differences between actual and predicted y
Step-by-step explanation:
The least squares regression method used in predictive modeling for linear regression models produces a best fit line which will minimize the square of the mean difference between the actual and projected or predicted values of the dependent, y variable. Hence, the when the sum of the squared value of the difference between the actual and predicted values (residual) are taken, the fit which gives the minimum sum of squared value is the best fit line upon which the estimated regression equation is based.
Answer:
g < 10
Step-by-step explanation:
-6g + 3g + 12 > -18
Combine like terms
-3g +12 > -18
Subtract 12 from each side
-3g+12-12 > -18-12
-3g > -30
Divide each side by -3, remembering to flip the inequality
-3g/-3 < -30/-3
g < 10
Answer:
B
Step-by-step explanation:
Answer:
25i
Step-by-step explanation:
Your calculator or your knowledge of powers of 5 will tell you that √625 is 25. The minus sign makes the root imaginary.
The answer is 59.6 because I divided 298 by 5
Hope this helps!!
