<h3>Answer:
10000 in base 5</h3>
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Explanation:
4+1 = 5 in base 10
But in base 5, the digit "5" does not exist.
The only digits in base five are: 0, 1, 2, 3, 4
This is similar to how in base ten, the digits span from 0 to 9 with the digit "10" not being a thing (rather it's the combination of the digits "1" and "0" put together).
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Anyways let's go back to base 5.
Instead of writing 4+1 = 5, we'd write 4+1 = 10 in base 5. The first digit rolls back to a 0 and we involve a second digit of 1.
Think how 9+1 = 10 in base 10.
Similarly,
44+1 = 100 in base 5
444+1 = 1000 in base 5
4444+1 = 10000 in base 5
and so on.
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Here are the first few numbers in base 5, when counting up by 1 each time.
0, 1, 2, 3, 4,
10, 11, 12, 13, 14,
20, 21, 22, 23, 24,
30, 31, 32, 33, 34,
40, 41, 42, 43, 44,
100, 101, 102, 103, ...
Notice each new row is when the pattern changes from what someone would expect in base 10. This is solely because the digit "5" isn't available in base 5.
Answer:
Ratio 1= 14:6
Ratio 2=21:9
Ratio 3=28:12
Step-by-step explanation:
7:3
7×2=14
3×2=6
=14:6
7×3=21
3×3=9
=21:9
7×4=28
3×4=12
=28:12
Answer:
B 1/3
Step-by-step explanation:
3^-3 * 3^8
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3^6
We know that a^b * a^c = a^(b+c)
3^(-3+8)
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3^6
3^(5)
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3^6
We know that a^b divide by a^c = a^(b-c)
3^(5-6)
3^-1
A negative exponent means it goes in the denominator of the fraction
1/3^1
1/3
Answer:
The approximate probability that the mean of the rounded ages within 0.25 years of the mean of the true ages is P=0.766.
Step-by-step explanation:
We have a uniform distribution from which we are taking a sample of size n=48. We have to determine the sampling distribution and calculate the probability of getting a sample within 0.25 years of the mean of the true ages.
The mean of the uniform distribution is:
The standard deviation of the uniform distribution is:
The sampling distribution can be approximated as a normal distribution with the following parameters:
We can now calculate the probability that the sample mean falls within 0.25 from the mean of the true ages using the z-score: