You do the things in the parentheses first then multiply them by 2
Answer:
The mean of W is 55 ounces.
The standard deviation of W is 4.33 ounces.
Step-by-step explanation:
Let X: weight of a red delicious apple, and B: the weight of the box and packing material.
The distribution that will represent W: the total weight of the packaged 5 randomly selected apples will be also normally distributed.
Applying the property of the mean:
, the mean of W will be:

Applying the property of the variance:
, the variance of W will be:

The mean standard deviation of W will be the squared root of V(W):

The mean of W is 55 ounces.
The standard deviation of W is 4.33 ounces.
Answer:
1
Step-by-step explanation:
By gradient, if you mean the "slope" of the linear function, then you have to find two points of the graph and use the "rise over run strategy". Given two coordinates, (x1, y1) and (x2, y2) of a linear function in the form y=mx+b, the slope of the line is (y2-y1)/(x2-x1). This shows the amount of "rise", or the vertical change, and the amount of "run", which is the horizontal change. Rise/Run gives the steepness of the line. The slope can also be modeled by Δy/Δx, which is the change in y over the change in x
Plugging in the given points (0,5) and (-5,0):
(y2-y1)/(x2-x1)= (5-0)/(0-(-5)) = 5/5 = 1