Answer:
d) Squared differences between actual and predicted Y values.
Step-by-step explanation:
Regression is called "least squares" regression line. The line takes the form = a + b*X where a and b are both constants. Value of Y and X is specific value of independent variable.Such formula could be used to generate values of given value X.
For example,
suppose a = 10 and b = 7. If X is 10, then predicted value for Y of 45 (from 10 + 5*7). It turns out that with any two variables X and Y. In other words, there exists one formula that will produce the best, or most accurate predictions for Y given X. Any other equation would not fit as well and would predict Y with more error. That equation is called the least squares regression equation.
It minimize the squared difference between actual and predicted value.
Answer:
1,2,4,8,16,32
Step-by-step explanation:
power of two sequence
Answer:
There was a 25% increase.
Step-by-step explanation:
50 =2×5×5
125=5×5×5
Hoghest common factor = 5×5
=25
Answer:
The total value of the discount was $10.80.
Step-by-step explanation:
Since we are finding the value of the discount, we just need to find 18% of 60.
We can convert 18% into a decimal.
18%=0.18
Multiply.
0.18*60=10.8
The total value of the discount was $10.80.
