Math 342 syllabus and datasets

unit date topics class datasets hw datasets
Introduction 5 Feb F Welcome    
    Confirmatory vs. Exploratory statistics Mammalian brains  
  8 Feb M Principles    
    Confirmatory vs. Exploratory statistics Mammalian brains  
    Pattern vs. Deviation    
    Presentation vs. Discovery Who makes lunch?  
Statistics   Sampling distributions    
review   Population vs. samples    
    parameters vs. statistics    
    Sampling distributions Larry, Mary… Used cars
  10 Feb W Sampling distributions, cont'd Unemployment rate  
    The expected value and variance Men's weights  
    Hypothesis tests    
    Hypothesis testing and p-values ESP CD mastering
  12 Feb F Testing and confidence intervals    
    The one sample t-test Body temperature  
    Confidence intervals (t) for the mean    
    Intervals and tests    
  15 Feb M Lab assignment: Data Desk tutorial    
    The Data Desk interface and principles Forbes 500 companies  
Univariate 17 Feb W Extending the histogram    
displays   Histograms and choice of settings Tipping CEO golf handicaps
    Density estimation: basic ideas Web times  
  22 Feb M Density estimation    
    Adaptive and nearest-neighbor methods Web times  
    Testing for multiple modes    
  26 Feb F Displaying distributions    
    Stem-and-leaf plots Mantle and Mays  
    Principles: Multifunctioning plot elements    
    Principles: Display vs. Reduction    
    Quantiles and percentiles    
    Boxplots   Salaries by majors
  1 Mar M Comparing distributions    
    Order statistics CEO golf handicaps,  
    Normal probability plots stock ratings Simulated NPP's
  3 Mar W Comparing distributions Math 143 survey  
    Q-Q plots for two datasets GRE scores GRE scores
    Displaying categorical data    
    Pie charts and bar charts    
  8 Mar M Displaying categorical data Education by state  
    Triaxial plots [Jorge Calvo] British elections  
  10 Mar W Displaying categorical data    
    Jittering Titanic survivors Siskel and Ebert
    Plot symbols    
Bivariate 12 Mar F Smoothing    
displays   Running medians: 4253H,twice Cow temperatures  
  15 Mar M Smoothing    
    Lowess Cow temperatures  
  17 Mar W Time series Investment dartboard Baseball standings
    Time series and smoothing Carbon dioxide  
    Banking to 45 Sunspots, Canadian lynx  
  19 Mar F Time series    
    The parallel lines optical illusion Investment dartboard  
    Cory, Patty: Siskel and Ebert    
  5 Apr M The regression model    
    Regression as least squares line US cities Chromatography
    Regression as conditional mean    
    The simple linear regression model    
  7 Apr W Assessing the regression model    
    Residual plots US cities  
    Correlation and R-squared Pizza prices  
    Conditional SD Girls' heights  
  9 Apr F Time Series    
    Kate, Tom: Baseball standings    
  12 Apr M The regression model    
    Inference for regression coefficients    
    The need for graphics Anscombe data  
    Regression: an example 100 meters  
  14 Apr W Transformations    
    When data don't fit the model Math 143 survey  
    Transforming right-skewed distributions Medicare  
    Logs and exponential growth US population  
  16 Apr F Transformations Mammalian brains  
    Theoretical models Forbes 500 companies  
    More on log transformations Tree volumes  
    Power transformations Gas mileage  
  19 Apr M Regression and residuals    
    Arjuna, Sarah: Chromatography    
  21 Apr W Multiple regression    
    The multiple regression model Heptathlon Airplane prices
    Geometry: fitting planes    
    Building a multiple regression model    
  23 Apr F Multiple regression    
    Collinearity Heptathlon  
    Model building    
    Interpreting regression coefficients    
    Indicator variables    
  26 Apr M Multiple regression    
    Partial regression plots Galapagos species  
    Model building: an example ozone hole  
Multivariate 30 Apr F Projection-based methods    
displays   3D rotating plots Companies Colleges
    Scatterplot matrices: brushing/slicing Random numbers  
    Trellis displays (coplots) NYC ozone  
  3 May M Parallel axis-based methods    
    Parallel axis plots Cars  
    The data image    
    Finding clusters    
  5 May W Icon-based methods    
    Color, plot symbols Companies  
    Hugo: Airplane prices    
  7 May F Icon-based methods    
    Classification and clustering Cars  
    Stars, profiles    
    Chernoff faces    
    Large datasets [Matt Hutcheson]    
    Collecting large datasets Non-white US population  
    Bandwidth-location plots    
    Animating trends over time    
Graphical 10 May M Graphical and information density    
principles   Data density examples from ads,  
    Data-ink ratio USA Today, Tufte, etc.  
    Chartjunk and ducks    
  12 May W Graphical deception    
    Misleading and lying graphics examples from ads,  
    Marlin, Sherman: Colleges Tufte, Wainer, etc.  
  14 May F Graphical insights    
    Two examples Napoleon's march  
    Chris: Good and bad graphics The Challenger disaster  


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