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Why you prefer Normal Distribution over the other distributions in Statistics?
For theoretical reasons (such as the central limit theorem), any variable that is the sum of a large number of independent factors is likely to be normally distributed. For this reason, the normal distribution is used throughout statistics, natural science, and social science as a simple model for complex phenomena.
Why you prefer normal distribution as compare to others in statistics?
Perhaps a mistaken impression, after completing an initial course in statistics, is that one distribution is better than another. Many other distributions exists. Usually, introductory statistics classes concern confidence limits, hypothesis testing and sample size determination which all involve a sampling distribution of a particular statistic such as the mean. The normal distribution is often the appropriate distribution in these areas. The normal distribution is appropriate when the random variable in question is the result of many small independent random variables that have been are summed . The attached link shows this very well. Theoretically, a random variable approaches the normal distribution as the sample size tends towards infinity. (Central limit theory) As a practical matter, it is very important that the contributing variables be small and independent.
What does mu mean in statistics?
Usually mu is the symbol for the mean of a probability distribution. It is sometimes used as the average of a dataset (also called the mean of the dataset), although I prefer to use "x bar".
Why are statistics rare for orchiectomies performed in connection with sex change procedures?
Statistics for orchiectomies in connection with gender reassignment surgery are difficult to establish because most patients who have had this type of surgery prefer to keep it confidential.
If a distribution is badly skewed researchers are more likely than usual to prefer the as a measure of central tendency?
This would be the average. When the numbers are all over the place, it is difficult to use them to come to conclusions.
