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What sample size is recommended in order to meet the assumption of a normal distribution even when the population of interest is not normal.?
The ideal sample size depends on a number of factors:
- how far from Normal the underlying distribution is.
- how close you need to get to a Normal distribution - in terms of the decision(s) that might be based on it and the cost of making an error.
- the rarity of the characteristic that you wish to study. (You might need a large sample just to ensure that you get representatives that have whatever characteristic you are studying.)
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When doing a t-test what does normal distributed in population mean?
It means that the random variable of interest is Normally distributed and so the t-distribution is an appropriate distribution for the test rather than just an approximation.
What is the population of interest in statistics?
It is the population which you are studying.
What is population interest?
The population of interest is the population you are trying to draw an inference about from the collected data sets. For example if you are interested in the average height of a college student on the east coast then the population of interest would be all college students on the east coast. If you are trying to find out the compressive strength of a certain concrete mixture then the population of interest is all types of concrete of this type.
How much will Pauline pay in interest if she takes out a simple interest loan with a principal of 3900.00 at 7 2 percent for 3 years?
Assumption: "7 2" is actually 7.2 Simple interest is simple. All you do is multiply the principal by the rate to get the yearly amount of interest. Therefore, 3900 times 7.2 is the same as $3900 x 0.072 = $280.80 per year interest. Since its over 3 years, just multiply by 3. Therefore, you get $280.80 x 3 = $842.40 in interest.
What is the shape of the binomial probability distribution in rolling a die?
The distribution depends on what the variable is. If the key outcome is the number on the top of the die, the distribution in multinomial (6-valued), not binomial. If the key outcome is the number of primes, composite or neither, the distribution is trinomial. If the key outcome is the number of sixes, the distribution is binomial with unequal probabilities of success and failure. If the key outcome is odd or even the distribution is binomial with equal probabilities for the two outcomes. Thus, depending on the outcome of interest the distribution may or may not be binomial and, even when it is binomial, it can have different parameters and therefore different shapes.
