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Section 5.1 ~ What is Normal? Introduction to Probability and Statistics Ms. Young ~ room 113.

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Presentation on theme: "Section 5.1 ~ What is Normal? Introduction to Probability and Statistics Ms. Young ~ room 113."— Presentation transcript:

1 Section 5.1 ~ What is Normal? Introduction to Probability and Statistics Ms. Young ~ room 113

2 Objective Sec. 5.1 In this section you will understand what is meant by a normal distribution and be able to identify situations in which a normal distribution is likely to arise.

3 Normal Distribution Sec. 5.1 A normal distribution has the following characteristics:  Single-peaked  Symmetric (mean and median are the same as the mode)  The curve is spread out in the shape of a bell (“bell-shaped” distribution)

4 Normal Distribution Cont’d… Sec. 5.1 All normal distributions have the same characteristic bell shape, but can differ in their mean and variation Knowing the mean and the standard deviation of a normal distribution tells you everything you need to know about its variation The following distributions have the same mean, but different standard deviations

5 The Normal Distribution and Relative Frequencies Sec. 5.1 The area that lies under the curve corresponding to a range of values on the x-axis is the relative frequency of those values The total area under the curve is 1, or 100% because the total relative frequency for the histogram is 1 or 100%

6 When Can We Expect a Normal Distribution? Sec. 5.1 Here are some common circumstances in which you can expect a normal distribution to occur:  Physical characteristics such as: Height, weight, blood pressure, & reflex times  Standardized test scores such as: SAT’s, IQ tests, PSSA’s, etc.  Sports statistics such as: Batting averages, times in swimming, results in a track meet, etc.

7 Summary Sec. 5.1 A distribution is likely to be normal if it satisfies the following criteria:  Most data values are clustered near the mean, giving the distribution a well defined single peak  Data values are spread evenly around the mean, making the distribution symmetric  Larger deviations from the mean become increasingly rare, producing tapering tails of the distribution (therefore creating the bell shape)  Individual data values result from a combination of many different factors, such as genetic and environmental factors


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