Pierre is running 26 and 2/10 miles in the marathon. he has ran 3/4 of the way. How far has he run?
1 answer:
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Answer:
10 terms
Step-by-step explanation:
equate the sum formula to 55 and solve for n
n(n + 1) = 55 ( multiply both sides by 2 to clear the fraction )
n(n + 1) = 110 ← distribute parenthesis on left side
n² + n = 110 ( subtract 110 from both sides )
n² + n - 110 = 0 ← in standard form
Consider the factors of the constant term (- 110) which sum to give the coefficient of the n- term (+ 1)
the factors are + 11 and - 10 , since
11 × - 10 = - 110 and 11 - 10 = + 1 , then
(n + 11)(n - 10) = 0 ← in factored form
equate each factor to zero and solve for n
n + 11 = 0 ⇒ n = - 11
n - 10 = 0 ⇒ n = 10
However, n > 0 , then n = 10
number of terms which sum to 55 is 10
Answer:
Let X the random variable who represents the file sizeof music. We know the following info:
We select a sample of n=50 nails. That represent the sample size.
Since the sample size is large enough n >30, we can use the central limit theorem. From this theorem we know that the distribution for the sample mean is given by:
And we can approximate the distribution of the sample mean as a normal distribution and no matter if the distribution for X is right skewed or no.
Step-by-step explanation:
Previous concepts
Normal distribution, is a "probability distribution that is symmetric about the mean, showing that data near the mean are more frequent in occurrence than data far from the mean".
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
Let X the random variable who represents the file sizeof music. We know the following info:
We select a sample of n=50 nails. That represent the sample size.
Since the sample size is large enough n >30, we can use the central limit theorem. From this theorem we know that the distribution for the sample mean is given by:
And we can approximate the distribution of the sample mean as a normal distribution and no matter if the distribution for X is right skewed or no.