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Statistica Textbook Examples
Computer-Aided Multivariate Analysis, Fourth Edition, by Afifi, Clark and May
Chapter 6: Simple linear regression and correlation

Page 87 Figure 6.1  Scatter diagram and regression line of FEV1 versus height for fathers in lung function data.

NOTE:  Throughout this chapter and the next, the variables FFEV1 and MFEV1 have been divided by 100 before use in analyses.  We have named these modified variables FFEV1a and MFEV1a, respectively.  

File
  Open - open the lung data set
Graph
  Scatterplots
    "Quick" tab
      Variables - choose fheight for the x-axis and ffev1a for the y-axis
        OK
          OK

We modified the graph by double clicking on the x-axis and modifying the range, which is under the "Scaling" tab.  You will need to change the mode from auto to manual first.  We edited the steps and then clicked on OK.  We modified the y-axis by clicking on it and then following the same steps.  We modified the title by double clicking on it.

Page 88  The descriptive statistics at the top of the page.

Statistics
  Basic Statistics
    Descriptive Statistics
      OK
        Variables - select fheight and ffev1a and uncheck the "minimum and maximum" box
          "Advanced" tab        
            Summary
Descriptive Statistics (lung.sta)
  Valid N Mean Std.Dev.
FHEIGHT 150 69.26000 2.779189
FFEV1a 150 4.09327 0.650752

Page 98 The correlation in the middle of the page

Statistics
  Basic Statistics
    Correlation matrices
      OK
        One variable list - select fheight and ffev1a
          OK
            Summary
Correlations (lung.sta) Marked correlations are significant at p < .05000 N=150 (Casewise deletion of missing data)
  FHEIGHT FFEV1a
FHEIGHT 1.000 0.504
FFEV1a 0.504 1.000

NOTE:  We modified the output to show one more decimal place by highlighting the cells and clicking on the .0 -> .00 button on the top menu.  Also, you can get the t-value by clicking on the "Options" tab and then clicking on "Display detailed summary of results" and "Summary".

Page 100 Table 6.2  ANOVA example from Figure 6.1

Statistics
  Advanced linear/non-linear models
    General regression models
      Simple regression
        OK
          "Quick" tab
            Variables - select ffev1a as the dependent variable and fheight 
            as the independent variable
              OK
                OK
RESULTS
  "Quick" tab
    All effects

NOTE:  We need to save the residuals from this regression for use in the next figure.  To do this:

RESULTS
  "Resids" tab
    Save - select all variables to be saved with the residuals
Test of SS Whole Model vs. SS Residual (lung.sta)
  Multiple R Multiple R2 Adjusted R2 SS Model df Model MS Model SS Residual df Residual MS Residual F p
FFEV1a 0.504396 0.254415 0.249378 16.05317 1 16.05317 47.04513 148 0.317872 50.50192 0.000000

Page 112 Figure 6.10  This has been skipped for now.

Page 116 Figure 6.12  Normal probability plot of the residuals of the regression of FEV1 on height for fathers in the lung function data.

Graphs
  2D graphs
    Normal probability plots
      "Quick" tab - select "Normal" for the graph type
        Variables - select ffevres1
          OK
            OK

As before, we modified the graph by double clicking on the x-axis and adjusting the range and step size.  We modified the title by double clicking on it.

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