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A histogram representing a sample taken from a population that is uniform?
For a large enough sample, it will resemble a rectangle whose base will be the range of the variable and the height will be the reciprocal of the number (or width) of the base.
Does the central limit theorem allows the use of the normal distribution to analyze the sample mean if the sample sizes are large enough?
Yes. Roughly, very large samples are very likely to have subsets data points having very similar means and distributions. Large numbers of such subsets will tend to be normal distributed (Why?) and will tend to make the total sample be normally distributed.
Why use sample instead of population?
When performing an experiment or gathering data for statistics, it would be very difficult to gather information for every member of the group's population. Instead, one can gather information from a sample large enough to be representative of the population.
Why does a statistical sample have to be large?
The larger the sample of data collected leads to a more accurate conclusion.
Characteristics of a good sample?
1. the sample should be representative thus carefully selected. 2. the sample should be adequate thus significant enough.
