Answer:
The ounces of oil needed is 5 ounces of oil
Step-by-step explanation:
The first thing to do here is to calculate the volume of the lemon-scented candle given.
Looking at shape the volume can be calculated using the formula L * B * H
where L(length) = 10cm , B(breadth) = 8cm and Height(h) = 25cm
The volume V is thus = 10 * 8 * 25 = 2,000 cm^3
The ounces of oil needed for the candle to have 0.0025 ounces of oil per cm^3 of wax will be = The volume of the lemon-scented candle * 0.0025 ounces of oil per cm^3 of wax
That will be = 0.0025 * 2,000 = 5 ounces
Answer:
3/4
Step-by-step explanation:
3/14 ÷ 2⁄7
Copy dot flip
3/14 * 7/2
We rewrite
3/2 * 7/14
Canceling a 7 from 7 and 14
3/2 * 1/2
Multiplying straight across
3*1 =3
2*2=4
3/4
Answer:

Step-by-step explanation:
Given:
The triangle is shown below.
We know that the sum of all interior angles of a triangle is equal to 180°.
Therefore,

Now, plugging the value of 'x' in each angle measure and determining its values. We get:

Therefore, the value of 'x' is 36° and the measure of the three angles are 36°, 71° and 73°.
Answer:
For the exponential distribution:


We know that the exponential distribution is skewed but the sample mean for this case using a sample size of 60 would be approximately normal, so then we can conclude that if we have a sample size like this one and an exponential distribution we can approximate the sample mean to the noemal distribution and indeed use the Central Limit theorem.



Step-by-step explanation:
The central limit theorem states that "if we have a population with mean μ and standard deviation σ and take sufficiently large random samples from the population with replacement, then the distribution of the sample means will be approximately normally distributed. This will hold true regardless of whether the source population is normal or skewed, provided the sample size is sufficiently large".
For this case we have a large sample size n =60 >30
The exponential distribution is the probability distribution that describes the time between events in a Poisson process.
For the exponential distribution:


We know that the exponential distribution is skewed but the sample mean for this case using a sample size of 60 would be approximately normal, so then we can conclude that if we have a sample size like this one and an exponential distribution we can approximate the sample mean to the noemal distribution and indeed use the Central Limit theorem.


