From Simulations to the Central Limit Theorem

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Presentation transcript:

From Simulations to the Central Limit Theorem

Parameter: A number describing a characteristic of the population (usually unknown) Statistic: A number describing a characteristic of a sample. Let’s review some vocabulary

In Inferential Statistics we use the value of a sample statistic to estimate a parameter value.   POPULATION: ALL Montgomery College students and estimate their mean height

We want to estimate the mean height of MC students. Will x-bar be equal to mu? What if we had selected another sample? What is the variability of the x-bars about the mean mu? What if we get another sample, will x-bar be the same?

What does the x-bar distribution look like?

How do we investigate the behavior of x-bar? WHY WORRIED ABOUT PROBABILITIES? In inferential statistics we test claims about population means by using probabilities

Graph the x-bar distribution and find its mean and standard deviation