5x-3=21-x
6x=24
X=4
You simply have to isolate the variable and then divide by 6 so that x is completely alone.
Answer:
Discarding the influential outlying cases when detected is also known as flagging outliers in a data set, and this is because outliers do not follow the rest of the dataset's pattern. if this outliers are not discarded they would have a negative effect on any model attached to the dataset
Step-by-step explanation:
In a regression class ; If extremely influential outlying cases are detected in a Data set, discarding this influential outlying cases is the right way to go about it
Discarding the influential outlying cases when detected is also known as flagging outliers in a data set, and this is because outliers do not follow the rest of the dataset's pattern. if this outliers are not discarded they would have a negative effect on any model attached to the dataset
<span>Brenda would be correct, another way to find the answer would be to use the keep change flip method. Where you keep 5/2 change division to multiplication then flip 4/1.
The equation would then be 5/2 * 4/1 then you just multiply straight across 5*4 = 20 and 2*1 equals 2. You end up with 20/2 which reduces to 10</span>
P(defective) = 3/12 = 1/4
P(good) = 1 - 1/4 = 3/4
The probability that at least 2 units are good is given by:
P(2 good) + P(3 good) + P(4 good) = 0.211 + 0.422 + 0.316 = 0.949.
