Since the slope is rise/run, 1/6 goes up one, right 6. Perpendicular is opposite that. so a slope of -6 goes down 6 and right 1. (as a fraction it's -6/1)
(1,-1)(2,2)
slope = (2 - (-1) / (2 - 1) = 3/1 = 3
y = mx + b
slope(m) = 3
use either of ur points...(2,2)...x = 2 and y = 2
now we sub and find b, the y int
2 = 3(2) + b
2 = 6 + b
2 - 6 = b
-4 = b
so ur equation is : y = 3x - 4
Answer:
the chances are 5/11 that Jones will get an orange and 5/11 that Beth will get an orange also
Step-by-step explanation:
For this problem, it can be solved by forming two equations. The first equation is the area of the original rectangle. Let l be the length and w be the width. l x w = 72 will be 1st equation. Then, the 2nd equation is 3.5l * 3.5w = A. By substitution, the new area, A = 12.25( l x w) = 12.25 (72) = 882 in<span>².</span>
Answer:
The probability table is shown below.
A Poisson distribution can be used to approximate the model of the number of hurricanes each season.
Step-by-step explanation:
(a)
The formula to compute the probability of an event <em>E</em> is:

Use this formula to compute the probabilities of 0 - 8 hurricanes each season.
The table for the probabilities is shown below.
(b)
Compute the mean number of hurricanes per season as follows:

If the variable <em>X</em> follows a Poisson distribution with parameter <em>λ</em> = 7.56 then the probability function is:

Compute the probability of <em>X</em> = 0 as follows:

Compute the probability of <em>X</em> = 1 as follows:

Compute the probabilities for the rest of the values of <em>X</em> in the similar way.
The probabilities are shown in the table.
On comparing the two probability tables, it can be seen that the Poisson distribution can be used to approximate the distribution of the number of hurricanes each season. This is because for every value of <em>X</em> the Poisson probability is approximately equal to the empirical probability.