Um... how am i supposed to know
No. The variance of any distribution is the sum of the squares of the deviation from the mean. Since the square of the deviation is essentially the square of the absolute value of the deviation, that means the variance is always positive, be the distribution normal, poisson, or other.
A chi-squared test is any statistical hypothesis test in which the sampling distribution of the test statistic is a chi-squared distribution when the null hypothesis is true.
Yes
The characteristics of the chi-square distribution are: A. The value of chi-square is never negative. B. The chi-square distribution is positively skewed. C. There is a family of chi-square distributions.
No.
the standard deviation of the population(sigma)/square root of sampling mean(n)
The Poisson distribution is a discrete distribution, with random variable k, related to the number events. The discrete probability function (probability mass function) is given as: f(k; L) where L (lambda) is the mean and square root of lambda is the standard deviation, as given in the link below: http://en.wikipedia.org/wiki/Poisson_distribution
No. The variance of any distribution is the sum of the squares of the deviation from the mean. Since the square of the deviation is essentially the square of the absolute value of the deviation, that means the variance is always positive, be the distribution normal, poisson, or other.
A probability sampling method is any method of sampling that utilizes some form of random selection. See: http://www.socialresearchmethods.net/kb/sampprob.php The simple random sample is an assumption when the chi-square distribution is used as the sampling distribution of the calculated variance (s^2). The second assumption is that the particular variable is normally distributed. It may not be in the sample, but it is assumed that the variable is normally distributed in the population. For a very good discussion of the chi-square test, see: http://en.wikipedia.org/wiki/Pearson%27s_chi-square_test
A chi-squared test is any statistical hypothesis test in which the sampling distribution of the test statistic is a chi-squared distribution when the null hypothesis is true.
Well, sort of. The Chi-square distribution is the sampling distribution of the variance. It is derived based on a random sample. A perfect random sample is where any value in the sample has any relationship to any other value. I would say that if the Chi-square distribution is used, then every effort should be made to make the sample as random as possible. I would also say that if the Chi-square distribution is used and the sample is clearly not a random sample, then improper conclusions may be reached.
The posterior plane is the one that is in the back. If you have a square it would be the back of it.
z=(x-mean)/(standard deviation of population distribution/square root of sample size) T-score is for when you don't have pop. standard deviation and must use sample s.d. as a substitute. t=(x-mean)/(standard deviation of sampling distribution/square root of sample size)
The sampling error is inversely proportional to the square root of the sample size.
Do you think square would fit your posterior.
Yes
Do you think square would fit your posterior.