# Multivariate Quantitative Relationships

• ### What is Statistics?

These pages from the University of Melbourne explain statistical concepts using various examples from medicine, science, sports, and finance. The intent is not computational skill but conceptual understanding. Some pages also contain data.
• ### Normal Approximation to Poisson Distribution

This applet demonstrates the Normal approximation to the Poisson Distribution. Users can set the rate, lambda (‘é), and the number of trials, n, and observe how the shape of the distribution changes. The Poisson distribution is shown in blue, and the Normal distribution is shown in red.
• ### Confidence Intervals

This applet introduces the concept of confidence intervals. Select an alpha level, sample size, and the number of experiments, and click "Play." For each sample, the applet will show the data points as blue dots and the confidence interval as a red, vertical line. The true population mean is shown as a horizontal purple line, and green ovals indicate which intervals do not contain the true mean.
• ### Choosing the Right Test

This page helps readers know which statistcal tests are appropriate for the different types of data. Two charts display the information. A discussion of study design and sample size, as well as exercise questions with solutions are also provided.
• ### Analysis Tool: T-Distribution Table

This page provides a t-table with degrees of freedom 1-30, 60, 120, and infinity and seven levels of alpha from .1 to .0005.

• ### Analysis Tool: Normal Distribution Table

This page provides a z-table with alpha levels from .00 to .09.

• ### Introduction to Simple Linear Regression

This page explains simple linear regression with an example on muscle strength versus lean body mass.
• ### Linear Regression and Best Fit

This lesson introduces simple linear regression with several Excel spreadsheet examples such as temperature versus cricket chirps, height versus shoe size, and laziness versus amount of TV watched. These activities require class participation.
• ### Analysis Tool: Multiple Linear Regressions

This online calculator allows users to enter 16 observations with up to 4 dependent variables and calculates the regression equation, the fitted values, R-Squared, the F-Statistic, mean, variance, first order serial-correlation, second order serial-correlation, the Durbin-Watson statistic, and the mean absolute errors. It also tests normality and gives the i-th residuals.

• ### Multiple Regression

This resource explains Multiple Regression and concepts associated with it. Key Words: Predicted values; Residuals; Dummy Variables; Interaction Effects; T-Test; Regression Coefficients; Correlation; Partial Correlation; R-Squared; Adjusted R-Squared; Multicollinearity; Variance-Inflation Factors; Transformation; Cook's Distance; Validity; Durbin-Watson Coefficient.