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Anton [14]
3 years ago
8

How do I turn this equation from standard form to slope intercept form?

Mathematics
1 answer:
Alina [70]3 years ago
7 0

y=-5/6x-7/3

Hope Your Thanksgiving Goes Well, Here's A Turkey

-TheKoolKid1O1

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Who baked more cookies per batch?
Gnom [1K]
Jenny does, she bakes 12 for every x and dan bakes 10 for every x.
So in conclusion jenny bakes more cookies per batch
5 0
3 years ago
Read 2 more answers
Two points A and B on a plan represent two localities 12 m apart. Given that the segment AB is 6cn long, find the scale used to
natka813 [3]

Answer:

The scale is 1:200

Step-by-step explanation:

On the plan we have the drawing as 6 cm

In real representation, we have the distance as 12 m

Firstly we have to convert to same unit

In this case, we use the cm for convenience

Mathematically, 100 cm is 1 m

Thus, 12 m

will be 12 * 100 = 1,200 cm

So, we have the ratio as;

6 cm : 1,200 cm

and that is 1:200 (since 6/1200 = 1/200 and in ratio form, we have that as 1:200)

7 0
3 years ago
Let X denote the time from the present until the stock market hits 25,000. If X ≤ 1, you win $10, 000X. If X > 1, you win not
const2013 [10]

Answer: $6321

Step-by-step explanation:

Expected value is given as exactly what you might think it means intuitively, the return you can expect for some type of action.

The basic expected value formula is the probability of an event multiplied by the amount of times the event happens:(P(x) * n).

he formula for the Expected Value for a binomial random variable is:

P(x) * X.

X is the number of trials and P(x) is the probability of success.

The formula for calculating the Expected Value where there are multiple probabilities is:

E(X) = ∑X * P(X)

The equation is basically the same, but here you are adding the sum of all the gains multiplied by their individual probabilities instead of just one probability.

Calculating the expected value of winning as follows:

Given,

Fx= e^-x, x is greater or equal to 0

Now, P less than or equal to zero =

[-e^-x] ^1

e^-0 - e^-1

= 1 - e^-1

= 0.6321

and P(x>1) = 1-0.6321= 0.3679

Therefore,Let y= amount of winnings.

Based on the above given information,

y= $10000 0

P(y)= 0.6321 0.3679

The expected value of winning:

E(y) = ΣyP(y)

E(y) = 10000 × 0.6321 + 0 × 0.3679

E(y) = $6321

Therefore, the expected value of winning is $6321

5 0
3 years ago
Brenda took out a personal loan for $12,000 at an interest rate of 12% compounded monthly. She made arrangements to pay the loan
iragen [17]

Answer: her monthly payments would be $267

Step-by-step explanation:

We would apply the periodic interest rate formula which is expressed as

P = a/[{(1+r)^n]-1}/{r(1+r)^n}]

Where

P represents the monthly payments.

a represents the amount of the loan

r represents the annual rate.

n represents number of monthly payments. Therefore

a = $12000

r = 0.12/12 = 0.01

n = 12 × 5 = 60

Therefore,

P = 12000/[{(1+0.01)^60]-1}/{0.01(1+0.01)^60}]

12000/[{(1.01)^60]-1}/{0.01(1.01)^60}]

P = 12000/{1.817 -1}/[0.01(1.817)]

P = 12000/(0.817/0.01817)

P = 12000/44.96

P = $267

7 0
3 years ago
A research team at Cornell University conducted a study showing that approximately 10% of all businessmen who wear ties wear the
LenKa [72]

Answer:

a) The probability that at least 5 ties are too tight is P=0.0432.

b) The probability that at most 12 ties are too tight is P=1.

Step-by-step explanation:

In this problem, we could represent the proabilities of this events with the Binomial distirbution, with parameter p=0.1 and sample size n=20.

a) We can express the probability that at least 5 ties are too tight as:

P(x\geq5)=1-\sum\limits^4_{k=0} {\frac{n!}{k!(n-k)!} p^k(1-p)^{n-k}}\\\\P(x\geq5)=1-(0.1216+0.2702+0.2852+0.1901+0.0898)\\\\P(x\geq5)=1-0.9568=0.0432

The probability that at least 5 ties are too tight is P=0.0432.

a) We can express the probability that at most 12 ties are too tight as:

P(x\leq 12)=\sum\limits^{12}_{k=0} {\frac{n!}{k!(n-k)!} p^k(1-p)^{n-k}}\\\\P(x\leq 12)=0.1216+0.2702+0.2852+0.1901+0.0898+0.0319+0.0089+0.0020+0.0004+0.0001+0.0000+0.0000+0.0000\\\\P(x\leq 12)=1

The probability that at most 12 ties are too tight is P=1.

5 0
3 years ago
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