1.3 notes

# 1.3 notes - STAT3000 Section 1.3 The Normal Distributions...

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STAT3000 Section 1.3: The Normal Distributions Exploring Data on a Single Quantitative Variable 1. Always plot your data: make a graph, usually a histogram or a stemplot. 2. Look for the overall pattern (shape, center, spread) and for striking deviations such as outliers. 3. Calculate a numerical summary to briefly describe center and spread. Sometimes the overall pattern of a large number of observations is so regular that we can describe it by a smooth curve = density curve . A density curve is a curve that is always on or above the horizontal axis ( they will not touch the horizontal axis ), and has area exactly 1 underneath it. A density curve describes the overall pattern of a distribution. The area under the curve and above any 33

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range of values is the proportion of all observations that fall in that range. If X is approximately normal, then X has a bell-shaped density curve. The density curve is perfectly symmetric about its mean μ . Its spread is determined by σ {notation X~ N( μ , σ )( variable x is aprox normal and( mean and std deviation for X)}. The total area under any normal curve is 1 (1 = 100%). 68-95-99.7 Rule There are an infinite number of normal curves, one for each pair of μ and σ . The standard normal is one very
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## This note was uploaded on 06/05/2011 for the course STAT 3000 taught by Professor Staff during the Spring '08 term at UGA.

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1.3 notes - STAT3000 Section 1.3 The Normal Distributions...

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