answersLogoWhite

0

Still curious? Ask our experts.

Chat with our AI personalities

JudyJudy
Simplicity is my specialty.
Chat with Judy
ViviVivi
Your ride-or-die bestie who's seen you through every high and low.
Chat with Vivi
LaoLao
The path is yours to walk; I am only here to hold up a mirror.
Chat with Lao

Add your answer:

Earn +20 pts
Q: What is the meaning of drop size in distribution?
Write your answer...
Submit
Still have questions?
magnify glass
imp
Continue Learning about Math & Arithmetic

Normal curve is the meaning of standard normal distribution?

No, the normal curve is not the meaning of the Normal distribution: it is one way of representing it.


What is sample distribution?

Theoretically, it is the distribution of a statistic based on all possible samples of a given size. In practice, it may be the distribution under repeated samples.


What does when the sample size and degrees of freedom is sufficiently large the difference between a t distribution and the normal distribution becomes negligible mean?

The t-distribution and the normal distribution are not exactly the same. The t-distribution is approximately normal, but since the sample size is so small, it is not exact. But n increases (sample size), degrees of freedom also increase (remember, df = n - 1) and the distribution of t becomes closer and closer to a normal distribution. Check out this picture for a visual explanation: http://www.uwsp.edu/PSYCH/stat/10/Image87.gif


How many microliters are in one drop?

The size of a drop depends on the surface tension of the liquid (and gravity). A standard medicinal drop 50 microlitres.


When population distribution is right skewed is the sampling also with right skewed distribution?

If the population distribution is roughly normal, the sampling distribution should also show a roughly normal distribution regardless of whether it is a large or small sample size. If a population distribution shows skew (in this case skewed right), the Central Limit Theorem states that if the sample size is large enough, the sampling distribution should show little skew and should be roughly normal. However, if the sampling distribution is too small, the sampling distribution will likely also show skew and will not be normal. Although it is difficult to say for sure "how big must a sample size be to eliminate any population skew", the 15/40 rule gives a good idea of whether a sample size is big enough. If the population is skewed and you have fewer that 15 samples, you will likely also have a skewed sampling distribution. If the population is skewed and you have more that 40 samples, your sampling distribution will likely be roughly normal.