Using the diagram, which fraction is equivalent to 1?

mariarad [96]

Answer:

≈ 16 g

Step-by-step explanation:

Half life of a radioactive isotope is the time it takes for a quantity of the isotope to be reduced to half of its initial mass.

Therefore;

New mass = Original mass × (1/2)^n, where n is the number of half lives

Thus;

New mass = 125 × (1/2)³

= 125/8

= 15.625

≈ 16 g

8 0

4 years ago

Can Somebody Please Explain How To Do It? THANKS

sergejj [24]

Hello from MrBillDoesMath!

Answer:

9

Discussion:

Solution 1:

Distance between two points (x1, y1), (x2,y2) is given by the formula

sqrt( (x1-x2)^2 + (y1-y2)^2). In our case this becomes

sqrt( (0-0)^2 + (12 -3)^2 ) =

sqrt( 9^2) =

9.

Solution 2:

Note points D and E both have x = 0 so segment DE is a vertical segment. The length is simply the difference of the y coordinates: 12- 3 = 9 as before.

Thank you,

MrB

6 0

3 years ago

PT. 4 OF MY HW! STILL UNIT RATE

satela [25.4K]

Answer: plant 1 grows at a faster rate

Step-by-step explanation:

5 0

3 years ago

The body temperatures of adults are normally distributed with a mean of 98.6degrees° F and a standard deviation of 0.60degrees°

Schach [20]

Answer:

97.72% probability that their mean body temperature is greater than 98.4degrees° F.

Step-by-step explanation:

To solve this question, we have to understand the normal probability distribution and the central limit theorem.

Normal probability distribution:

Problems of normally distributed samples can be 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.

Central limit theorem:

The Central Limit Theorem estabilishes that, for a random variable X, with mean $\mu$ and standard deviation $\sigma$ , the sample means with size n of at least 30 can be approximated to a normal distribution with mean $\mu$ and standard deviation $s = \frac{\sigma}{\sqrt{n}}$