What’s is 8.478 in expanded from

A 4-pound bag of sugar contains 454 one-teaspoon servings and costs $3.49. A batch of muffins uses 1/4 cup of sugar. How many ba

Mazyrski [523]

48/4 = 12 teaspoons per each batch

454/12 = 37.83 batches can be made

3.49/37.83 = 0.092$ per each batch

5 0

4 years ago

A chemical engineer is trying to increase the amount of the useful product in a reaction. She performs the reaction with her new

Natali5045456 [20]

Answer:

I think ur missing the actual data mate

Step-by-step explanation:

8 0

3 years ago

Read 2 more answers

Aria studied the traffic trends in India. She found that the number of cars on the road increases by 10% each year. If there wer

denpristay [2]

Answer:

8,800,000cars

Step-by-step explanation:

Given the initial amount of cars = 80,000,000

If there is 10 % increase in the first year;

Increment = 10% of 80,000,000

Increment = 0.1 * 80,000,000

Increment = 8,000,000

Amount of car in year 2 = 80million + 8million = 88million

Year3;

Amount of car in year 3 = 88,000,000+(10%of88million)

Amount of car in year 3 = 88,000,000+8,800,000

Amount of car in year 3 =96,800,000

Differences in the number of cars = 96,800,000 - 88,000,000

Differences in the number of cars = 8,800,000cars

Hence there are 8,800,000cars in years 3 than year 2

7 0

3 years ago

based on the simulation, what is the probability that at most 2 of the next 10 callers will have to wait more than 8 minutes to

Triss [41]

Using the binomial distribution, supposing that 0.3 of the callers have to wait more than 8 minutes to have their calls answered, it is found that there is a 0.3828 = 38.28% probability that at most 2 of the next 10 callers will have to wait more than 8 minutes to have their calls answered.

For each caller, there are only two possible outcomes, either they have to wait more than 8 minutes to have their calls answered, or they do not. The probability of a caller having to wait more than 8 minutes is independent of any other caller, which means that the binomial distribution is used to solve this question.

Binomial probability distribution

$P(X = x) = C_{n,x}.p^{x}.(1-p)^{n-x}$