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:
this is ez
Step-by-step explanation:
2.5 g converted to kg: 2.5 g x 1 kg/1000 g = 0.0025 kg = 2.5x10-3 kg
cm3 converted to m3: 1 cm3 x 10-6 m3/cm3 = 1x10-6 m3
Thus, the conversion of 2.5 g/cm3 to kg/m3 would be 2.5x10-3 kg/10-6 m3 = 2.5x103 kg/m3 = 2500 kg/m3
Answer:
basically u have to beble gep
Step-by-step explanation:
art