Answer:
The residual value is the difference between the observed value (from the scatter plot) and the predicted value (from the line of best fit).
Step-by-step explanation:
The residual value is the difference between the observed value (from the scatter plot) and the predicted value (from the line of best fit).
Residual Value = Observed Value - Predicted Value
<em>Since the residual value of -4.5 is negative, we can say the predicted value is larger than the observed value. In other words, the line of best fit is "above" the scatter plot point in that specific point.</em>
Answer:
123.8
Step-by-step explanation:
nearest tenth is 7 and the sixes aftr it are over half of a full decimal, so they round to 123.8
5.
f(K) = D^3 => f(25) = 125 => 25 * t = 125 ( because K is directly proportional with D^3 )=> t = 125 / 25 => t = 5 => f(25) = 25 * 5 => K * 5 = D^3 ;
6.
f(L) = F^3 => f(2) =3^3 =>f(2) = 27 => 2 / t =27 => t = 2 / 27 => t = 0.074 => f(2) = 2 / 0.074 => K / 0.074 = F^3 ;
Answer: Theoretical- In a perfect world everything is a 50/50 chance and experimental is real world and the probability is not 50/50.
Step-by-step explanation:
No. If she selects a breakfast at random there is an equal chance she will select each item. 25% chance she will select oatmeal, 25% chance she will select cereal, 25% she will select french toast, and a 25% chance she will select scrambled eggs.
