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3 years ago

5

Define slope intersect

2 answers:

Delicious77 [7]3 years ago

5 0

A line that goes through the x axis or y axis

Vanyuwa [196]3 years ago

4 0

I think you meant intercept and not intersect but the definition is the equation of a straight line in the form y = mx + b where m is the slope of the line and b is its y-intercept

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An object falls 9 m in the first second, another 27 m in the second second, and then 108 m more in the third second. If this pat

aev [14]

Answer: B) 684m

Step-by-step explanation:

From 9 to 27 is a 3 times increase, from 27 to 108 is a 4 times increase. So following the pattern, we can determine that it will increase 5 times, and fall another 540m in second 4. Then, we simply add all the numbers together to get the answer!

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3 years ago

which expression is equivalent to (^3sqrtm)^7 in exponential form? a) 7 m/3 b) 3 m/7 c) m 3/7 d) m 7/3

Komok [63]

$(\sqrt[3]{m})^{7} = m^{ \frac{7}{3}}$

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3 years ago

Round 4,398,202 to the nearest 100

Klio2033 [76]

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3 years ago

Read 2 more answers

Help for lots of points

Stells [14]

Answer:

45

Step-by-step explanation:

i hope this helps you :) i would do the middle one but you dont need that one

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3 years ago

Read 2 more answers

John and Jane are married. The probability that John watches a certain television show is .7. The probability that Jane watches

ikadub [295]

a) The probability that both John and Jane watch the show is 0.12.

b.The probability that Jane watches the show, given that John does is 0.1714.

c)They do watch show independent of each other.

Step-by-step explanation:

Here, as given in the question:

Probability that John watches a certain show = 0.7 ⇒ P(J) = 0.7

Probability that Jane watches a certain show = 0.3 ⇒ P(Je) = 0.3

Probability that John watches a certain show given Jane watches it to

= 0.4 ⇒ P(J/Je) = 0.4

a. ) Here, we need to find the probability of both Jane and John watching a show , P(J∩Je)

Now, by BAYES THEOREM:

$P(J/Je) = \frac{P(J \cap Je)}{P(Je)}$

$\implies 0.4 = \frac{P(J \cap Je)}{0.3} \\\implies P(J \cap Je) = 0.4 \times 0.3 = 0.12$

Hence the probability that both John and Jane watch the show is 0.12.

b.) The probability that Jane watches the show, given that John does is P(J/Je)

By BAYES Theorem:

$P(Je/J) = \frac{P(J \cap Je)}{P(J)}\\\implies P(Je/J) = \frac{0.12}{0.7} = 0.1714$

Hence, the probability that Jane watches the show, given that John does is 0.1714.

c) As we can see P(Jane ∩ John) = 0.12

So, the probability of both of them seeing the show TOGETHER is 0.12.

Hence, they do watch show independent of each other and the probability of doing that is 1.0.12 = 0.88

7 0

3 years ago