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andrew11 [14]
3 years ago
5

How many positive integers n satisfy the following condition: (130n)^50 > n^100 >2^200

Mathematics
2 answers:
brilliants [131]3 years ago
8 0

Answer:

27

Step-by-step explanation:

kenny6666 [7]3 years ago
4 0

Answer:

27

Step-by-step explanation:

You might be interested in
Angle JKL is 54 degrees. What is the measure of angle MKL? *
hoa [83]

Answer:

MKL = 36°

Step-by-step explanation:

(3x + 6) + (6x + 12) = 54°

3x + 6x + 6 + 12 = 54

9x + 18 = 54

9x = 54 - 18

9x = 36

x = 36/9

x = 4

MKL = 6x + 12

MKL = 6(4) + 12

MKL = 24 + 12

MKL = 36°

6 0
3 years ago
on opening day the new in and out took 38 minutes to go through the drive-thru yesterday it took 16 minutes find the percent of
Kruka [31]
One moment, i wills answer soon working on it
3 0
3 years ago
Helpp me out pls!!!!!!!!!
dsp73

Answer:

a. Maurice walked farther.

b. 0.62 m

Step-by-step explanation:

Maurice

4.1 × 1.8 = 7.38 miles

Junnie

2.5 × 3.2 = 8 miles

This shows that Junnie walked more than Maurice.

8 - 7.38 = 0.62

Junnie walked 0.62 m more than Maurice

5 0
3 years ago
Help me solve this problem please
mel-nik [20]
It’s only a vertical angle
7 0
2 years ago
A manager at a local company asked his employees how many times they had given blood in the last year. The results of the survey
Lubov Fominskaja [6]

Answer:

Var(X) = E(X^2) -[E(X)]^2 = 4.97 -(1.61)^2 =2.3779

And the deviation would be:

Sd(X) =\sqrt{2.3779}= 1.542 \approx 1.54

Step-by-step explanation:

For this case we have the following distribution given:

X        0         1       2       3       4         5        6

P(X)  0.3   0.25   0.2   0.12   0.07   0.04   0.02

For this case we need to find first the expected value given by:

E(X) = \sum_{i=1}^n X_i P(X_I)

And replacing we got:

E(X)= 0*0.3 +1*0.25 +2*0.2 +3*0.12 +4*0.07+ 5*0.04 +6*0.02=1.61

Now we can find the second moment given by:

E(X^2) =\sum_{i=1}^n X^2_i P(X_i)

And replacing we got:

E(X^2)= 0^2*0.3 +1^2*0.25 +2^2*0.2 +3^2*0.12 +4^2*0.07+ 5^2*0.04 +6^2*0.02=4.97

And the variance would be given by:

Var(X) = E(X^2) -[E(X)]^2 = 4.97 -(1.61)^2 =2.3779

And the deviation would be:

Sd(X) =\sqrt{2.3779}= 1.542 \approx 1.54

 

8 0
3 years ago
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