Test #1 Review
I. Descriptive statistics
Graphical:
Histogram
Numerical:
Mean, Variance, Standard deviation
Range (Ex. 1.17)
Empirical rule
II. Probability
Probability models  discrete case
Experiments
Sample space  outcomes
Probability function  axioms
Counting methods
Product rule
Permutations
Combinations, binomial coefficients
Conditional probability
Independent events
Laws of probability
Multiplication law
Additive law
Law of total probability
Bayes’ law
Simple Random Samples
III. Discrete Random Variables
Probability distribution
Expected value and Variance
Theorems on expected value of functions of a random variable
Special distributions
Binomial
Geometric
Negative binomial
Hypergeometric
Poisson
Moment generating functions
Tchebysheff’s Theorem
IV. Statistical methods
Statistically significant results (Example 3.8, p.105)
Method of maximum likelihood (Example 3.10, p.109)
V. Miscellaneous topics
Capturerecapture method (hypergeometric distribution, Exercise 3.120, p.130)
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 Fall '09
 Snyder
 Statistics, Empirical Rule, Probability, Standard Deviation, Variance, Probability theory, Probability Probability models

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