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2 years ago

(1 point)

Mathematics

1 answer:

Alex73 [517]2 years ago

7 0

Answer:

had to add it here bit. ly 3a7A8h

Step-by-step explanation:

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PLS HELP MEEE PICTURE BELOW

Leviafan [203]

Answer:

h = 3.6

Step-by-step explanation:

This is just substituting in for variables and solving for x. The hard part is knowing the formula.

R = h((a+b)/2) where a and b are the 2 different bases, h is the height or latitude, and R is the area of a trapezoid, is the formula.

Given that R = 8.1, a = 1 and b = 3.5, we can substitute these equations in the formula.

(8.1) = h(((1) + (3.5)) / 2)

= h((4.5) / 2)

= h(2.25)

8.1/2.25 = h

3.6 = h

5 0

2 years ago

What is the product?<br><br> (5.63 x 10^5) x 5,600,000

victus00 [196]

Answer: $3.1528 \times 10^{12}.$

Step-by-step explanation: Given expression $(5.63 \times 10^5) \times 5,600,000$ .

In order to find the product of given expression, we need to convert 5,600,000 into scientific notation, because other number is also in scientific notation.

5,600,000 = 5.6 × 10^6.

Therefore, $(5.63 \times 10^5) \times 5,600,000 =(5.63 \times 10^5) \times (5.6 \times 10^6)$ .

Now, multiplying 5.63 × 5.6 first, we get 31.528.

And 10^5 × 10^6 = 10^11.

Therefore,

$(5.63 \times 10^5) \times (5.6 \times 10^6) = 31.528 \times 10^11$ .

6 0

2 years ago

Suppose that the walking step lengths of adult males are normally distributed with a mean of 2.5 feet and a standard deviation o

Hitman42 [59]

Answer:

0.0668 = 6.68% probability that an individual man’s step length is less than 1.9 feet.

Step-by-step explanation:

Normal Probability Distribution:

Problems of normal distributions can be solved using the z-score formula.

In a set with mean $\mu$ and standard deviation $\sigma$ , the z-score 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 p-value, we get the probability that the value of the measure is greater than X.

Normally distributed with a mean of 2.5 feet and a standard deviation of 0.4 feet.

This means that $\mu = 2.5, \sigma = 0.4$