Eliza’s backpack weighs 18 and StartFraction 7 over 9 EndFraction pounds with her math book in it. Without her math book, her ba

700,000 * 45%
700,000 *.45 = 315,000
Final audience is 315,000

Utilizing the normal distribution and the central limit theorem, there's a 0.0284 or 2.84% chance of observing a sample mean mass of 695g or less.

Answer:

The chance of completing the entire package installation in under 12 minutes is 0.1271.

Step-by-step explanation:

We define X as a normal distribution representing the time taken in seconds to install the software. According to the Central Limit Theorem, X is approximately normal, where the mean is 15 and variance is 15, giving a standard deviation of √15 = 3.873.

To find the probability of the total installation lasting less than 12 minutes, which equals 720 seconds, each installation should average under 720/68 = 10.5882 seconds. Thus, we seek the probability that X is less than 10.5882. To do this, we will apply W, the standard deviation value of X, calculated via the formula provided.

Utilizing , we reference the cumulative distribution function of the standard normal variable W, with values found in the attached file.

Given the symmetry of the standard normal distribution density function, we ascertain .

Consequently, the probability that the installation process for the entire package is completed within 12 minutes is 0.1271.

Initially, we need to determine how fast he skis in a minute without considering any speed increase.
To do that, we'll divide the total distance by the time.
960 divided by 5 equals 192.
Therefore, his speed is 192 meters per second.
Now, let's add 20 to this figure.
192 plus 20 equals 212.
Now, to calculate how far he can travel in 10 minutes, we multiply 212 by 10.
212 times 10 equals 2120.
Thus, Alex can cover 2120 meters in 10 minutes.

We understand that the workforce increases twofold every week.

This means that the workforce from the previous week is precisely 50% of the current week's total.

Hence, it took a total of 11 weeks for the factory to reach half of its full capacity.