Fundamental Statistics for the Behavioral Sciences:

Seeing Statistics

This page contains applets from McClelland's Seeing Statistics, which have been integrated with material in Fundamental Statistics for the Behavioral Sciences, (5th edition) by David C. Howell. You merely need to click on the appropriate link to open the applet, and then follow the directions on the page.

These applets will run best if you have Sun's Java Virtual Machine installed on your computer. You can very easily download that software for free by going to clicking on the following image. Just follow their instructions. (Be patient at first--it can take a while for the first image to load.)

Chapter 4:

• Brightness Matching Experiment

Chapter 5:

• Why Divide by N-1?

Chapter 6:

• Normal Distribution and z- Scores

Chapter 8:

• Testing a Simple Null Hypothesis

Chapter 9: Correlation

• Construction of scatter diagrams:
  • CorrelationPoints allows user to click on a scatter diagram to add data points with the correlation coefficient automatically updated with each new point.
  • PointRemove allows the user to remove individual observations from the data and observe the effect on the correlation coefficient.

• Link between degree of scatter and correlation coefficient:
  • CorrelationPicture allows user to use a slider to change the degree of the scatter in the diagram and observe the corresponding change in the correlation coefficient. There are versions with and without the regression line superimposed on the data.
• Factors that affect the correlation:
  • RangeRestrict allows user to move sliders to restrict the range on a scatter plot with the old and new correlations being displayed.
  • Heterogeneous subsamples allows the user to examine the relationship between X and Y when the data are composed of heterogeneous sets of observations. This builds on the relationship seen in Figure 9.8

• Predicting Y allows you to use a slider to vary the value of X and read off the predicted value of Y. You can then change the slope and intercept and notice the changes that these actions produce.

• Finding the best fitting line

• Influential data points

• Testing the slope with t

  • The t distribution under the null hypothesis

  • Calculating t

• Sampling distribution of the mean allows you to examine how sample means vary over repeated sampling.

• Comparing z and t. illustrates the difference between the two distributions as a function of the degrees of freedom.

• Confidence Interval for the Mean illustrates what is meant by a confidence interval.

• Distribution of differences between means shows the population distributions, sampling distribution of the mean for each, and the sampling distribution of the differences between means.

• t-test on differences between means allows you to vary means, standard deviations, or n and see the results in terms of t and its associated probability.

• Factors that affect power lets you adjust those variables that have an effect on power, and observe the result.

• F probabilities is an applet that lets you see how the sample distribution of F changes as you change the degrees of freedom for the numerator and denominator.

Chapter 17: Factorial Analysis of Variance

• Graphing interactions illustrates main effects and interactions, and shows how one can change without the other.

• MosaicTwoWay is an applet that allows you to change the entries in a contingency table and observe the effects on chi-square.

 Return to index