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grigory [225]
3 years ago
6

Find the secound derivative of f(x)= x√x+3

Mathematics
1 answer:
8090 [49]3 years ago
3 0
F(x) = x^(3/2) +3
f'(x) = (3/2)x^(1/2)
f''(x) = (1/2)*(3/2)*x^(-1/2)

f''(x) = 3/(4√x)

_____
If you mean f(x) = x√(x+3), parentheses are needed (or you need to typeset the expression).
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According to the National Vital Statistics, full-term babies' birth weights are Normally distributed with a mean of 7.5 pounds a
Sav [38]

Answer:

68.26% probability that a randomly selected full-term pregnancy baby's birth weight is between 6.4 and 8.6 pounds

Step-by-step explanation:

Problems of normally distributed samples are solved using the z-score formula.

In a set with mean \mu and standard deviation \sigma, the zscore of a measure X is given by:

Z = \frac{X - \mu}{\sigma}

The Z-score measures how many standard deviations the measure is from the mean. After finding the Z-score, we look at the z-score table and find the p-value associated with this z-score. This p-value is the probability that the value of the measure is smaller than X, that is, the percentile of X. Subtracting 1 by the pvalue, we get the probability that the value of the measure is greater than X.

In this problem, we have that:

\mu = 7.5, \sigma = 1.1

What is the probability that a randomly selected full-term pregnancy baby's birth weight is between 6.4 and 8.6 pounds

This is the pvalue of Z when X = 8.6 subtracted by the pvalue of Z when X = 6.4. So

X = 8.6

Z = \frac{X - \mu}{\sigma}

Z = \frac{8.6 - 7.5}{1.1}

Z = 1

Z = 1 has a pvalue of 0.8413

X = 6.4

Z = \frac{X - \mu}{\sigma}

Z = \frac{6.4 - 7.5}{1.1}

Z = -1

Z = -1 has a pvalue of 0.1587

0.8413 - 0.1587 = 0.6826

68.26% probability that a randomly selected full-term pregnancy baby's birth weight is between 6.4 and 8.6 pounds

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3 years ago
Classify the model as exponential growth or exponential decay. Identify the growth or decay factor AND the percent of increase o
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See also brainly.com/question/8975313

The growth factor is 1.05.

The increase is (1.05 -1)*100% = 5% per period.
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