Lecture 21 - 211 Fall 2009

Lecture 21 - 211 Fall 2009 - I. Introduction II....

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± 1 I. Introduction II. Descriptive Statistics III. Probability, Random Variables and Sampling Distributions. A. Probabilty (Chapter 5) B. Random Variables (Chapter 5) C. Normal Distribution (Chapter 6) D. Sampling Distribution (Chapter 7) Binomial Random Variables ± Binomial Distribution – use the formulas: • Probabilities: Mean (Center) EX np μ == () ( 1 ) nx n x x Px C p p =− 3. Binomial Distributions • Mean (Center) • Standard Deviation (Variation) [ ] x (1 ) x p npq σ =⋅ Binomial Distribution ± Constants of the Binomial Formula: • Two parameters: • If we know p and n, we know :
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± 2 x P( x ) 0 1 2 3 4 Probability Distribution: x = # correct guesses on 10 T/F questions. p = 0.5; what do we know about the distribution? 5 6 7 8 9 10 How many P( )s do you need to calculate? Probabilities equal Areas of Bars on Histograms. ± P( X = x ) = area of a histogram bar. • The width is “1.” The width is “1.” • Area is equal to height, or probability. Area is equal to height, or probability.
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Lecture 21 - 211 Fall 2009 - I. Introduction II....

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