You can show it 4 ways by rotating the paper and if that is not an option, then the answer is 2.
You factor the expression first leaving you with

Then you would cancel out 3xy as because there is exactly one on each side. This, in turn, would leave you with
z - 1
<span>Probability = 0.063
Fourth try = 0.0973
Let X be the number of failed attempts at passing the test before the student passes. This
is a negative binomial or geometric variable with x â {0, 1, 2, 3, . . .}, p = P(success) = 0.7
and the number of successes to to observe r = 1. Thus the pmf is nb(x; 1, p) = (1 â’ p)
xp.
The probability P that the student passes on the third try means that there were x = 2
failed attempts or P = nb(2, ; 1, .7) = (.3)2
(.7) = 0.063 . The probability that the student
passes before the third try is that there were two or fewer failed attmpts, so P = P(X ≤
2) = nb(0, ; 1, .7) + nb(1, ; 1, .7) + nb(2, ; 1, .7) = (.3)0
(.7) + (.3)1
(.7) + (.3)2
(.7) = 0.973 .</span>
There are 125 refrigerators in total.
Explanation:
Set up an equation:
x(.40)= 50
, where x is the number of refrigerators
Solve for x
Answer/Step-by-step explanation:
To represent the data given on a stem and leaf plot, the whole number in a given value would be used as the stem, while the number after the decimal point is the leaf. (Key: 3|3 = 3.3).
For example, in the first stem in the first row, we have 4 as the stem. All values that starts with 4 point would be represented in this row. The digit after 4 point for each of the values would be written on the leaf column in the first row, from the least to the largest. For the first row we have: 4 | 3 9.
Same applies to the rest rows.
The stem plot would look like the one below:
Ice Thickness:
Stem | Leaf
4 | 3 9
5 | 1 8 8 8 9
6 | 5 8 9 9
7 | 0 2 2 2 2 5 9
8 | 0 7
The data of the stem-and-leaf plot shows a bell-shaped pattern with majority of the ice thickness for the 20 locations clustering around the center of the data distribution.