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kramer
4 years ago
15

What is log Subscript 15 Baseline 2 cubed rewritten using the power property?

Mathematics
2 answers:
nalin [4]4 years ago
7 0

Answer:

The equivalent expression

Step-by-step explanation:

Assuming your expression is \log_{15}2^3, then we can use the power property of logarithm , which is \log_ab^n=n\log_ab.

If we let a=15, b=2, and n=3

Then using the power property of logarithm will give us:

\log_{15}2^3=3\log_{15}2

Using the power property of logarithm, the equivalent expression is 3\log_{15}2

garri49 [273]4 years ago
5 0

Answer:

D

Step-by-step explanation:

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8 0
4 years ago
Please help me ASAP!! I will give Brainliest!!
topjm [15]

Answer:

Mountain peek

Step-by-step explanation:

Pyramid like structure

3 0
3 years ago
Read 2 more answers
Suppose that 11 inches of wire costs 66 cents. at the same rate, how much (in cents) will 4 inches of wire cost?
Andre45 [30]
24 cents.

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(proportions)

hope this is clear :))
7 0
4 years ago
The product of twice a number and 7 less than the number
garik1379 [7]

Answer:

i believe the answer is 6

Step-by-step explanation:

i'm not entirely sure but i hope this helps :)

have a nice day !!

**please let me know if this was wrong**

4 0
3 years ago
Suppose that are Yi.....Yn are i.i.d random variables with a Nâ(âμY, Ï^2Y â) distribution. How would the probability density of
svp [43]

Answer:

b. As the sample size â increases, the variance of decreases. â So, the distribution of becomes highly concentrated around.

Step-by-step explanation:

Let : Yi,.... Yn are = i.i.d are random variables. The probability density of the distribution varies along with the sample size. When the sample size changes, the probability density of $E^3$ also changes.

The probability distribution may be defined as the statistical expression which defines the likelihood of any outcome for the discrete random variable and it can be opposed to the continuous random variable.

In the context, when the size of the sample of the distribution size increases, it causes a decrease in the variance and so the distribution becomes highly concentrated around.

5 0
3 years ago
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