Review for Exam I — Chapters 1
∼
4
1
Descriptive Statistics
•
Categorical variables and quantitative variables
•
Graphical methods
–
bar graph and pie chart
–
histogram [shape characteristics: symmetric?, skewed?, multimodal?]
–
stemandleaf display
–
boxplot [5number summary]
•
Numerical measures
–
Measures of location
*
Typical values (center): sample mean, sample median [their robustness against
outliers]
*
percentiles, quartiles
–
Measures of variation (spread)
*
sample variance, sample standard deviation, sample range, interquartile range
2
Probability
•
Random process, sample space, outcome, event
•
Basic set theory (union, intersection, complement, mutually exclusive)
•
Interpretation of probability
•
Axioms and properties of probability
•
Conditional probability
•
Independence
•
Law of total probability
•
Bayes rule
•
series system and parallel system
1
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3
Discrete Random Variables
•
Probability mass function (pmf) of a discrete rv and requirements of a pmf
•
Cumulative distribution function (cdf) of a discrete rv
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 Spring '07
 Parzen
 Statistics, Normal Distribution, Probability theory, Discrete Probability Distributions, continuous probability distributions, Discrete RV, continuous RV

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