First, "boxes of two sizes" means we can assign variables: Let x = number of large boxes y = number of small boxes "There are 115 boxes in all" means x + y = 115 [eq1] Now, the pounds for each kind of box is: (pounds per box)*(number of boxes) So, pounds for large boxes + pounds for small boxes = 4125 pounds "the truck is carrying a total of 4125 pounds in boxes" (50)*(x) + (25)*(y) = 4125 [eq2] It is important to find two equations so we can solve for two variables. Solve for one of the variables in eq1 then replace (substitute) the expression for that variable in eq2. Let's solve for x: x = 115 - y [from eq1] 50(115-y) + 25y = 4125 [from eq2] 5750 - 50y + 25y = 4125 [distribute] 5750 - 25y = 4125 -25y = -1625 y = 65 [divide both sides by (-25)] There are 65 small boxes. Put that value into either equation (now, which is easier?) to solve for x: x = 115 - y x = 115 - 65 x = 50 There are 50 large boxes.
90 degrees means 90 degrees counterclockwise. So from the fourth quadrant we'll end up in the first quadrant. X and Y get swapped and one negated, it must be the -2 becoming 2, so our image is
(2,5)
Answer: A
Answer:
I know (B) is correct, the median is the best measure of center if t distribution is Skewed Left
Step-by-step explanation:
Answer:
If you mean |x| and |-x| yes they are equal.
Step-by-step explanation:
Brackets do not exactly specify the meaning of absolute value.
On most keyboards, above the enter button on the main keyboard part (not the keypad one) there is a back slash symbol \ and if you hold shift, there might be another symbol | which more accurately represents absolute value,
If you aren't talking about the absolute value, then no.
Answer:
a) 615
b) 715
c) 344
Step-by-step explanation:
According to the Question,
- Given that, A study conducted by the Center for Population Economics at the University of Chicago studied the birth weights of 732 babies born in New York. The mean weight was 3311 grams with a standard deviation of 860 grams
- Since the distribution is approximately bell-shaped, we can use the normal distribution and calculate the Z scores for each scenario.
Z = (x - mean)/standard deviation
Now,
For x = 4171, Z = (4171 - 3311)/860 = 1
- P(Z < 1) using Z table for areas for the standard normal distribution, you will get 0.8413.
Next, multiply that by the sample size of 732.
- Therefore 732(0.8413) = 615.8316, so approximately 615 will weigh less than 4171
- For part b, use the same method except x is now 1591.
Z = (1581 - 3311)/860 = -2
- P(Z > -2) , using the Z table is 1 - 0.0228 = 0.9772 . Now 732(0.9772) = 715.3104, so approximately 715 will weigh more than 1591.
- For part c, we now need to get two Z scores, one for 3311 and another for 5031.
Z1 = (3311 - 3311)/860 = 0
Z2 = (5031 - 3311)/860= 2
P(0 ≤ Z ≤ 2) = 0.9772 - 0.5000 = 0.4772
approximately 47% fall between 0 and 1 standard deviation, so take 0.47 times 732 ⇒ 732×0.47 = 344.
