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Unformatted text preview: Statistics 528 - Lecture 5 1 Statistics 528 - Lecture 5 Professor Kate Calder 1 Section 1.3 cont. Normal Distributions All normal distributions have the same shape - symmetric, unimodal, bell-shaped The mean ( ) and standard deviation ( ) completely specify a normal density curve. The mean ( ) is the center of the curve. Note: mean = median (since the normal density curve is symmetric) Statistics 528 - Lecture 5 Professor Kate Calder 2 The standard deviation ( ) is the point at which the curve changes from falling more steeply to falling less steeply (point at which the curvature changes) Statistics 528 - Lecture 5 Professor Kate Calder 3 Two normal curves Statistics 528 - Lecture 5 Professor Kate Calder 4 Why the normal curve? 1. Good distribution for summarizing real data- exam scores- repeated measurements- characteristics of biological populations 2. Good approximation to chance outcomes- tossing coins 3. Statistical Inference (Central Limit Theorem) HOWEVER, not all data is normal! Always do EDA before using the normal distribution. Statistics 528 - Lecture 5 Professor Kate Calder 5 Relative Frequencies 68-95-99.7 Percent Rule For a normal distribution with mean and standard deviation , approximately 68% of the observations fall within of the . approximately 95% of the observations fall within 2 of the ....
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This note was uploaded on 07/26/2011 for the course STA 528 taught by Professor Calder during the Winter '09 term at Ohio State.
- Winter '09