IQ is normally distributed in the general population. Age is not.
I am under the assumption that in statistics, if the ten percent condition is not met, meaning that the sample size is more than 10% of the population, then the result is not a normal distribution.
It is called a normal distribution.
we prefer normal distribution over other distribution in statistics because most of the data around us is continuous. So, for continuous data normal distribution is used.
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.
IQ is normally distributed in the general population. Age is not.
Why we prefer Normal Distribution over the other distributions in Statistics
In statistics, a quartile is each of four equal groups into which a population can be divided according to the distribution of values of a particular variable.
Kenneth Hadden has written: 'The elderly population of Connecticut, 1980' -- subject(s): Older people, Social conditions, Statistics 'The population of Connecticut, 1970: age and sex composition' -- subject(s): Age distribution (Demography), Sex, Statistics, Vital Statistics 'The elderly population of Connecticut, 1970' -- subject(s): Older people, Statistics
I am under the assumption that in statistics, if the ten percent condition is not met, meaning that the sample size is more than 10% of the population, then the result is not a normal distribution.
It is called a normal distribution.
example of symmetrical distribution
Jacob S. Siegel has written: 'The demography and epidemiology of human health and aging' -- subject(s): Epidemiology, Health and hygiene, Age distribution (Demography), Population aging, Older people 'A generation of change' -- subject(s): Age distribution (Demography), Older people, Population, Social conditions, Statistics 'Demographic aspects of aging and the older population in the United States' -- subject(s): Older people, Statistics 'Coverage of the Hispanic population of the United States in the 1970 census' -- subject(s): Census, 19th, 1970, Hispanic Americans, Statistics 'The population of Hungary' -- subject(s): Population 'International trends and perspectives' -- subject(s): Age distribution (Demography), Aging, Older people, Statistics, Vital statistitics
μ is the symbol for the population mean in statistics. fyi and related but not necessary for the above answer: the sample mean is , enunciated by saying "x" bar. hope this helped. Citation : http://en.wikipedia.org/wiki/Arithmetic_mean
The question gives summary statistics for a population. If the underlying distribution is Gaussian, or some other known distribution, then the probability density function can be calculated. Even so, there is no question and so nothing to "solve".
Sampling distribution in statistics works by providing the probability distribution of a statistic based on a random sample. An example of this is figuring out the probability of running out of water on a camping trip.
we prefer normal distribution over other distribution in statistics because most of the data around us is continuous. So, for continuous data normal distribution is used.