Lesson 3.1: Normal Distribution

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Presentation transcript:

Lesson 3.1: Normal Distribution

Normal Distribution A bell-shaped probability distribution (shape) of data, that follows the following rules. a) Symmetric, with a central peak (mean & median& mode are the same) b) Follows the “68%, 95%, 99.7%” rule. This distribution occurs a lot in both natural and man-made phenomena

Examples of Normal Distributions

Examples of Normal Distributions

Normal Distribution The two “tails” of the graph will continue forever, however, if the data follows a normal distribution, the chances of getting a data value that far away from the mean is basically zero. For distribution of discrete data, any probabilities can be calculated by counting all the possible outcomes. For continuous distributions, we will calculate the area under the graph for the desired range of values (more on that in the next lessons).

Describing Distributions Mound Shaped (symmetric) Uniform

Describing Distributions Negatively (Left) Skewed Positively (Right) Skewed

Mean, Median and Mode in Skewed Distributions Positively Skewed Negatively Skewed

Bimodal Distribution This distribution may occur when a population consists of two groups with different attributes. i.e. Population shoe sizes can have 2 modes because men generally have larger feet than women. test 3

Practice Questions Worksheet on my website: #1 – 3 Look at proposal #2 on my website and start working on it.