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Chapter 5 Notes by Steven Grindle

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Data varies whether it be time, sugar content in cereal, blood pressure, body temperatures or weight of cola in cans.

From any list of data, measures of center (mean, median, mode, and midrange) and measures of spread (standard deviation, variance, range) can be made to characterize the distribution of the data. From now on, only the mean and standard deviation will be used.

Last chapter, we briefly reviewed the concept of Probability. Since the probability of flipping a coin and getting a "heads" is 50%, we would expect that 100 flips of a coin would produce about 50 "heads".

We would not be surprised we got 50, 51, 52, 53, 54, 55 "heads". We would be shocked if we got 95, 96, 97, 98, 99 or 100 "heads" even though we know it is possible. 55 "heads" is not unusual, 95 heads is very unusual.

At what number of "heads" in 100 coin flips do we declare an unusual event has occurred? at 60 heads? at 70 heads? at 80 heads? Right now we do not have a precise answer to this important question. Inferential statistics is designed to precisely answer this question!

Before I can show you how inferential statistics works, we need to understand Discrete Probability Distributions (Chapter 5).