Yes, but that begs the question: how large should the sample size be?
z- statistics is applied under two conditions: 1. when the population standard deviation is known. 2. when the sample size is large. In the absence of the parameter sigma when we use its estimate s, the distribution of z remains no longer normal but changes to t distribution. this modification depends on the degrees of freedom available for the estimation of sigma or standard deviation. hope this will help u.... mona upreti.. :)
There is a 95% probability that the true population proportion lies within the confidence interval.
The mean of the sampling distribution is the population mean.
No, as you said it is right skewed.
The sampling distribution for a statistic is the distribution of the statistic across all possible samples of that specific size which can be drawn from the population.
It can be.
You probably mean the confidence interval. When you construct a confidence interval it has a percentage coverage that is based on assumptions about the population distribution. If the population distribution is skewed there is reason to believe that (a) the statistics upon which the interval are based (namely the mean and standard deviation) might well be biased, and (b) the confidence interval will not accurately cover the population value as accurately or symmetrically as expected.
In a study using 9 samples, and in which the population variance is unknown, the distribution that should be used to calculate confidence intervals is
By definition, the 1st 6-tile is the point below which 1/6 of the population falls (irrespective of which distribution is involved). The 2nd 6-tile is the point below which 2/6 of the population falls. This is 100 * 1/3 ~ 33.3% of the population.
normal distribution
It depends whether or not the observations are independent and on the distribution of the variable that is being measured or the sample size. You cannot simply assume that the observations are independent and that the distribution is Gaussian (Normal).
Population distribution refers to the patterns that a population creates as they spread within an area. A sampling distribution is a representative, random sample of that population.
10,486.22 this is the density population and this is the distribution population 2,00465.789
Population distribution is usually greatly affected by what?
yea
Population distribution is the way a population is apread out over an area.
Population distribution is mapped by geographers all over the world or Population distribution is observed daily by geographers.