Please help me, I don't understand this-

What is minimal completion time for the activities in the graph below? In a complete sentence, explain how you got your answer

kupik [55]

The minimal completion time for the activities is the shortest possible time for all the activities to be finished. In doing this, we look at the path that would require the greatest amount of time. At the START node, we choose the path that would take the longest which is 7 days leading to ACTIVITY D. Next, we choose the path leading to ACTIVITY B which takes 5 days. Then, we move to ACTIVITY C taking 5 days and finally, reach the END which would take 6 days. So, the minimal completion time is:
7 + 5 + 5 + 6 = 23 days

6 0

4 years ago

Life Expectancies In a study of the life expectancy of people in a certain geographic region, the mean age at death was years an

Sphinxa [80]

Answer:

The probability that the mean life expectancy of the sample is less than X years is the p-value of $Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$ , in which $\mu$ is the mean life expectancy, $\sigma$ is the standard deviation and n is the size of the sample.

Step-by-step explanation:

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

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.

Central Limit Theorem

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

For a skewed variable, the Central Limit Theorem can also be applied, as long as n is at least 30.

We have:

Mean $\mu$ , standard deviation $\sigma$ .

Sample of size n:

This means that the z-score is now, by the Central Limit Theorem:

$Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$

Find the probability that the mean life expectancy will be less than years.

The probability that the mean life expectancy of the sample is less than X years is the p-value of $Z = \frac{X - \mu}{\frac{\sigma}{\sqrt{n}}}$ , in which $\mu$ is the mean life expectancy, $\sigma$ is the standard deviation and n is the size of the sample.

8 0

3 years ago

I need helping solving -3z+7=-7-10z

Tpy6a [65]

-3z + 7 = -7 - 10z

Add 10z to both sides

7z + 7 = -7

Subtract 7 from both sides

7z = -14

Divide by 7

Z = -2

8 0

4 years ago

Read 2 more answers

On a coordinate plane, a curved line crosses the y-axis at (0, 1), crosses the x-axis at (.25, 0), turns at point (2, negative 3

Artyom0805 [142]

Answer:

All real numbers greater than or equal to -3