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V125BC [204]
3 years ago
13

Need help on these two!!

Mathematics
1 answer:
pishuonlain [190]3 years ago
7 0

Answer:

The first one is false and the second is vertex

Step-by-step explanation:

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Approximately how long does it take a sample of francium-223 to decay by 50%?
valentina_108 [34]
B. 100 minutes correct me if i’m wrong
6 0
2 years ago
Solve the equation 2x^{2}+9x-1=x to the nearest 10th
Scilla [17]

Answer:

2x2+9x−1=x

Step 1: Subtract x from both sides.

2x2+9x−1−x=x−x

2x2+8x−1=0

Step 2: Use quadratic formula with a=2, b=8, c=-1.

x=

−b±√b2−4ac

2a

x=

−(8)±√(8)2−4(2)(−1)

2(2)

x=

−8±√72

4

x=−2+

3

2

√2 or x=−2+

−3

2

√2

Step-by-step explanation:

This is what I got but I'm not 100% positive. I checked it on a calculator and it seemed to check out.

4 0
3 years ago
What is the value of x in the equation 1/5 x-2/3 y=30 when y =15
laiz [17]
First replace y with 15.
1/5x-10=30
Then just solve from there.
x=200
4 0
3 years ago
Read 2 more answers
Help please!!! Will Mark Brainly!!!
Rudik [331]

Answer:

D

Step-by-step explanation:

5 0
3 years ago
The director of admissions at Kinzua University in Nova Scotia estimated the distribution of student admissions for the fall sem
wariber [46]

Answer:

In order to calculate the expected value we can use the following formula:  

E(X)=\sum_{i=1}^n X_i P(X_i)  

And if we use the values obtained we got:  

E(X)=(1060*0.5) +(1400*0.1) +(1620*0.4)=1318  

Step-by-step explanation:

Let X the random variable that represent the number of admisions at the universit, and we have this probability distribution given:

X        1060   1400    1620

P(X)     0.5      0.1        0.4

In statistics and probability analysis, the expected value "is calculated by multiplying each of the possible outcomes by the likelihood each outcome will occur and then summing all of those values".

The variance of a random variable Var(X) is the expected value of the squared deviation from the mean of X, E(X).

And the standard deviation of a random variable X is just the square root of the variance.  

In order to calculate the expected value we can use the following formula:  

E(X)=\sum_{i=1}^n X_i P(X_i)  

And if we use the values obtained we got:  

E(X)=(1060*0.5) +(1400*0.1) +(1620*0.4)=1318  

3 0
2 years ago
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