In Minitab Express, you get this sample by going to Data -> Generate Random Data. If you wish, you can get a normal curve superimposed on your histogram by drawing a histogram "With Fit" rather than a "Simple" histogram. Make a histogram, and you should see approximately a bell-shaped curve, although it will not be perfectly bell-shaped because it is a relatively small sample. Generate 100 rows of data and store the results in, say, C1. To see how they work, first take a sample of size 100 from a normal distribution by going to Calc -> Random Data -> Normal. Normal probability plots are useful for determining whether a distribution is approximately normal. You will not look at data until a bit later on. You should also gain experience in this lab in understanding when you should expect distributions to be normal.īegin this lab by opening up a blank Minitab worksheet. You will observe the Central Limit Theorem both by simulating random variables and by taking a sample from a real population. , X n are independent and identically distributed (i.i.d.) random variables with expected value μ and standard deviation σ, then the distribution of the mean of these random variables has approximately a normal distribution,with mean μ and standard deviation σ/√ n. The Central Limit Theorem states that if n is large and X 1, X 2. Math 11, Lab 6 Lab 6: Sampling distributions and the Central Limit TheoremIn this lab, you will explore the Central Limit Theorem, a result in probability theory that is that basis for most of the statistical inference techniques that we will study.
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