Module One: Exploring Data

Constructing and interpreting graphical displays of distributions of univariate data: Dotplot, stemplot, histogram, cumulative frequency plot Center and spread Clusters and gaps Outliners and other unusual features Shape

Summarizing distributions of univariate data: Measuring center: median, mean Measuring spread: range, interquartile range, standard deviation Measuring position: quartiles, percentiles, standardized scores (z-scores) Using box plots The effect of changing units on summary measures

Comparing distributions of univariate data: Dotplots, back-to-back stemplots, parallel boxplots Comparing center and spread: within group, between group variation Comparing clusters and gaps Comparing outliners and other unusual features Comparing shapes

Exploring bivariate data: Analyzing patterns in scatterplots Correlation and linearity Least-squares regression line Residual plots, outliners, and influential points Transformations to achieve linearity: logarithmic and power transformations

Exploring of categorical data: Frequency tables and bar charts Marginal and joint frequencies for two-way tables Conditional relative frequencies and association Comparing distributions using bar charts

  Constructing and interpreting graphical displays of distributions of univariate data:

• Dotplot, stemplot, histogram, cumulative frequency plot
• Center and spread
• Clusters and gaps
• Outliners and other unusual features
• Shape

  Summarizing distributions of univariate data:

• Measuring center: median, mean
• Measuring spread: range, interquartile range, standard deviation
• Measuring position: quartiles, percentiles, standardized scores (z-scores)
• Using box plots
• The effect of changing units on summary measures

  Comparing distributions of univariate data:

• Dotplots, back-to-back stemplots, parallel boxplots
• Comparing center and spread: within group, between group variation
• Comparing clusters and gaps
• Comparing outliners and other unusual features
• Comparing shapes

  Exploring bivariate data:

• Analyzing patterns in scatterplots
• Correlation and linearity
• Least-squares regression line
• Residual plots, outliners, and influential points
• Transformations to achieve linearity: logarithmic and power transformations

  Exploring of categorical data:

• Frequency tables and bar charts
• Marginal and joint frequencies for two-way tables
• Conditional relative frequencies and association
• Comparing distributions using bar charts

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