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3 years ago

An example of an equation that is a linear function explain why it is linear

1 answer:

5 0

One example of a linear equation is
y = 7x + 4 because the slope is a set number and the graphed version of the equation is a completely straight line.
Hope this helps!

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New codes to destroy the First Order are known to exist. With probability 0.6, the codes are hidden by Leia; with probability 0.

elixir [45]

Answer: (a). 0.62 (b). 0.53

Step-by-step explanation:

Let us start by defining some events seen:

Given;

L rep the event that codes hidden Leia

BB represents the codes hidden in BB-8

H is the event that codes hidden by Hah

C-3PO rep the codes hidden in C3PO

Giving the probabilities, we have that

P(L) = probability that codes are hidden by Leia = 0.6

P(H) = probability that codes are hidden by Hah = 0.4

where P(BB/L) = 70/10 i.e 70%

P(C-3PO/L) = 1 - P(BB/L) = 1 - 7/10 = 3/10

Also, P(BB/H) = 1/2 = P(C-3PO/H)

We can say that Han Solo is likely to hide them in aceta BB-8 and C-3PO

To begin,

(a). The question tell us to find the probability that the codes are with BB-8.

First of all, we find P(BB).

P(BB) = P(L)*P(BB/L) + P(H)*P(BB/H)

solving this we get

P(BB) = 0.6*7/10 + 0.4*1/2 = 0.62

Therefore, the probability that the codes are with BB-8 = 0.62

(b). The second question says;

Given that the codes are with C-3PO, what is the probability the codes were hidden by Han Solo?

This tell us to find P(H/C-3PO)

P(H/C-3PO) = P(C-3PO/H)*P(H) / P(C-3PO/H) + P(C-3PO/L)*P(L)

inputting the values gives us;

P(H/C-3PO) = 1/2 * 0.4 / ( 1/2 *0.4 + 3/10 *0.6) = 0.53

SO we have that the probability the codes were hidden by Han Solo = 0.53

cheers I hope this was helpful!!

3 0

3 years ago

What is 26 divided by 503?

Hatshy [7]

Answer:0.05168986083

Step-by-step explanation:

4 0

3 years ago

Read 2 more answers

A score that is three standard deviations above the mean would have a z score of

tia_tia [17]

The value of z-score for a score that is three standard deviations above the mean is 3.

In this question,

A z-score measures exactly how many standard deviations a data point is above or below the mean. It allows us to calculate the probability of a score occurring within our normal distribution and enables us to compare two scores that are from different normal distributions.

Let x be the score

let μ be the mean and

let σ be the standard deviations

Now, x = μ + 3σ

The formula of z-score is

$z_{score} = \frac{x-\mu}{\sigma}$