 Exploring
Data:
Describing
patterns and departures from patterns. Exploratory
analysis of data makes use of graphical and numerical
techniques to study patterns and departures from patterns. Emphasis
should be placed on interpreting information from graphical and
numerical displays and summaries.
 Constructing and
interpreting
graphical displays of
distributions of univariate data (dotplot, stemplot, histogram,
cumulative frequency plot)
 Constructing and
interpreting
graphical displays of
distributions of univariate data (dotplot, stemplot, histogram,
cumulative frequency plot)
 Summarizing distributions
of
univariate data
 Comparing
distributions
of univariate data (dotplots,
backtoback stemplots, parallel
boxplots)
 Exploring bivariate data
 Exploring categorical data
 Frequency
tables and bar charts
 Marginal and joint frequencies for twoway tables
 Conditional relative frequencies and association
 Comparing distributions using bar charts
 Sampling
and Experimentation:
Planning and conducting a study:
Data must be collected according to a welldeveloped plan if valid
information on a conjecture is to be obtained. This plan includes
clarifying the question and deciding upon a method of data collection
and analysis.
 Overview of methods
of data collection
 Planning and conducting
surveys
 Planning and conducting
experiments
 Generalizability of
results
and types of conclusions that
can be drawn from observational studies, experiments, and surveys
 Anticipating
Patterns: Exploring
random phenomena using
probability and simulation: Probability is the tool used for
anticipating what the distribution of data should look like under a
given model.
 Statistical
Inference:
Estimating population parameters and
testing hypotheses: Statistical inference guides the selection
of
appropriate models.

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