There are 360 degrees of longitude (0 to 180e and 0 to 180w). there are 24 hours in a day thus 24 times zones. therefore each time zone is degrees of longitude wide. "do the math" as they say: 360 divided by 24= also if each degree of longitude at the equator is roughly 60 miles wide then each time zone is approximately miles wide at the equator.

The vertical and horizontal imaginary lines that conform to the spherical shape of the Earth are called the longitudes and the latitudes, respectively. The purpose of these lines are to locate exactly the geographical location of every place on Earth. It's usually applied in aeronautics to aid them during their travels.

Since a sphere has a cross sectional area of a circle, it's revolution has a total of 360°. You should divide this evenly to the 24 existing time zones. Therefore, the angle measurement of the width of longitude for each time zone is 360°/24 = 15°. Each time zone has 15° width of longitude.

For the second question, we use dimensional analysis. This approach is used when you cancel out units that appear both in the numerator and denominator side. The simplified unit should conform to what is asked. In this case, it should be miles per time zone. The solution is as follows:

60 miles/° longitude × 15° longitude/time zone = 900 miles/time zone

Thus, each time zone is approximately 900 miles wide at the equator.

The probability is

Step-by-step explanation:

Let's start by defining the random variable as :

'' The amount of gasoline sold each month to customers at Bob's Exxon station in downtown Navasota ''

Therefore, if is a continuous random variable that has a normal distribution, we write ~ ( μ , σ )

Where ''μ'' is the mean and ''σ'' is the standard deviation.

For the random variable we write :

~

We need to find

In order to calculate this, we are going to standardize the variable. This means, finding the equivalent probability in a normal random variable

~

We perform this because the random variable ~ is tabulated in any book or either you can find the table on Internet.

To standardize the variable we need to subtract the mean and then divide by the standard deviation ⇒

⇒ P[ (G - μ) / σ > ] ⇒

Because (G - μ) / σ  ~

Finally, ⇒ = 1 - Φ(2)

Where '' Ф(x) = '' represents the cumulative function of

Looking for  Φ(2) in any table,

≅ %2.28

We found out that the probability is