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2 years ago

A line passes through the points

Mathematics

1 answer:

murzikaleks [220]2 years ago

7 0

Answer:

Step-by-step explanation:

Slope, m =change in value of y on the vertical axis / change in value of x on the horizontal axis

change in the value of y = y2 - y1

Change in value of x = x2 -x1

y2 = final value of y

y 1 = initial value of y

x2 = final value of x

x1 = initial value of x

From the information given,

y2 = - a

y1 = a

x2 = 0

x1 = 0

Slope = (- a - a)/0-0 = -2a/0 = 0

2) equation of the line is represented in the slope intercept form as y = mx + c

Where

m = slope

c = intercept.

To determine c, we would substitute y = a, x = p and m = 0 into y= mx + c. It becomes

a = 0×p + c

c = a

The equation becomes

y = a

3) y intercept,c = a

4) the slope of a line perpendicular to the given line is a negative reciprocal of the slope of the given line. Therefore,

Slope = - 0 = 0

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2 years ago

Please Help with this Problem!

tatiyna

Answer: 3.5, 4.5, 9.5, 3.5

Step-by-step explanation:

Look at the image below to see where A, B, C, and D are.

A + B = 8

B + D = 8

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2 years ago

The number and frequency of Atlantic hurricanes annually from 1940 through 2007 is shown here:

klio [65]

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 E is:

$P(E)=\frac{Favorable\ no.\ of\ frequencies}{Total\ NO.\ of\ frequencies}$

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:

$E(X)=\frac{\sum x f_{x}}{\sum f_{x}}=\frac{176}{68}= 2.5882\approx2.59$

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

$P(X=x)=\frac{e^{-2.59}(2.59)^{x}}{x!} ;\ x=0, 1, 2,...$

Compute the probability of X = 0 as follows:

$P(X=0)=\frac{e^{-2.59}(2.59)^{0}}{0!} =\frac{0.075\times1}{1}=0.075$

Compute the probability of X = 1 as follows:

$\neq P(X=1)=\frac{e^{-2.59}(2.59)^{1}}{1!} =\frac{0.075\times7.56}{1}=0.1943$

Compute the probabilities for the rest of the values of X 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 X the Poisson probability is approximately equal to the empirical probability.

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3 years ago