Download Chapter Three: Numerically Summarizing Data

Chapter Three: Numerically Summarizing Data
Terminology:
parameter
degrees of freedom
statistic
z-score
mean
k th percentile
median
quartile
mode
decile
midrange
interquartile range (IQR)
multi-modal distribution
outlier
range
fences (lower and upper)
deviation about the mean
five-number summary
population variance
population standard deviation
boxplot
sample variance
empirical rule
sample standard deviation
Chebyshev’s inequality
Skills:
• Determine the measures of central tendency (mean, median, mode, midrange) from raw data
• Use the mean and median to help identify the shape of the distribution of data
• Determine the measures of dispersion (range, variance, standard deviation) from raw data
• Use the empirical rule to describe data that are bell-shaped
• Use Chebyshev’s Inequality to describe data from any distribution
• Determine the z-score of a data value and interpret this z-score
• Determine the data value of a given z-score
• Determine the k th percentile Pk data value using the formula for the index (similarly for
quartiles and deciles)
• Determine the percentile that corresponds to a given data value
• Interpret percentiles (quartiles and deciles)
• Determine the interquartile range (IQR) and lower and upper fences for a data set
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• Check a data set for outliers
• Construct a five-number summary for a data set
• Construct a boxplot for a data set
• Use the boxplot to help identify the shape of the distribution of data
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Chapter Five: Probability
Terminology:
experiment
disjoint events
outcome
complementary events
event
independent events
sample space
dependent events
impossible event
conditional probability
certainty
factorial
unusual event
permutation
mutually exclusive
combination
Skills:
• Understand and verify the properties of probabilities.
• Estimate probabilities from empirical data.
• Compute probabilities using the classical approach.
• Distinguish between mutually exclusive (disjoint) and non-mutually exclusive events.
• Calculate probabilities using the Addition Rule (for disjoint events) and the Generalized
Addition Rule.
• Calculate probabilities using the Complements Rule.
• Distinguish between dependent and independent events.
• Calculate probabilities using the Multiplication Rule (for independent events) and the Generalized Multiplication Rule.
• Calculate conditional probabilities.
• Determine the number of outcomes of an experiment using permutations (n Pr ) or combinations (n Cr ).
• Calculate probabilities of events using permutations or combinations.
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