The JCCKit is a small library and flexible framework for creating scientific charts and plots works on java platform.
The JCCKit is a small library and flexible framework for creating scientific charts and plots works on java platform.
When two variables are related, it is possible to predict a person's score on one variable from their score on the second variable with better than chance accuracy. This section describes how these predictions are made and what can be learned about the relationship between the variables by developing a prediction equation.
JFreeReport is a free Java report library. It has the following features: full on-screen print preview; data obtained via Swing's TableModel interface (making it easy to print data directly from your application); XML-based report definitions; output to the screen, printer or various export formats (PDF, HTML, CSV, Excel, plain text); support for servlets (uses the JFreeReport extensions) complete source code included (subject to the GNU Lesser General Public Licence); extensive source code documentation.
JFreeChart is a free Java class library for generating charts, including: pie charts (2D and 3D); bar charts (regular and stacked, with an optional 3D effect); line and area charts; scatter plots and bubble charts; time series, high/low/open/close charts and candle stick charts; combination charts; Pareto charts; Gantt charts; wind plots, meter charts and symbol charts; wafer map charts;
EXCITE is a collection of teaching materials developed by the Centers for Disease Control and Prevention (CDC) to introduce students to public health and epidemiology. Students will learn about the scientific method of inquiry, basic biostatistics, and outbreak investigation. EXCITE adapts readily to team teaching across a variety of subjects, including mathematics, social studies, history, and physical education.
A "12 page" tutorial that explores the liner models via excel spreadsheets. The learning module leads the user through various aspects of linear modeling. This tutorial includes a worksheet that allows students to vary the scatter (or noise) level, by adjusting the scroll bar or by clicking on the arrows, to see how the slope and intercept of line respond to the addition of scatter to the data, while monitoring the value of r^2.
A collection of Java applets and simulations covering a range of topics (descriptive statistics, confidence intervals, regression, effect size, ANOVA, etc.).
This page computes a variety of descriptive statistics and creates a stem and leaf plot. Enter data in the text area, specify a delimiter (Space, Return, Tab, New line), and click "Compute". The page returns sample size, mean, median, trimmed mean, trimean, minimum, maximum, range, first quartile, third quartile, semi-interquartile range, standard deviation, variance, standard error of the mean, skew, and kurtosis. Key Word: Calculator; Summary Statistics.
The Food and Drug Administration requires pharmaceutical companies to establish a shelf life for all new drug products through a stability analysis. This is done to ensure the quality of the drug taken by an individual is within established levels. The purpose of this out-of-class project or in-class example is to determine the shelf life of a new drug. This is done through using simple linear regression models and correctly interpreting confidence and prediction intervals. An Excel spreadsheet and SAS program are given to help perform the analysis. Key words: prediction interval, confidence interval, stability
This activity is an advanced version of the "Keep your eyes on the ball" activity by Bereska, et al. (1999). Students should gain experience with differentiating between independent and dependent variables, using linear regression to describe the relationship between these variables, and drawing inference about the parameters of the population regression line. Each group of students collects data on the rebound heights of a ball dropped multiple times from each of several different heights. By plotting the data, students quickly recognize the linear relationship. After obtaining the least squares estimate of the population regression line, students can set confidence intervals or test hypotheses on the parameters. Predictions of rebound length can be made for new values of the drop height as well. Data from different groups can be used to test for equality of the intercepts and slopes. By focusing on a particular drop height and multiple types of balls, one can also introduce the concept of analysis of variance. Key words: Linear regression, independent variable, dependent variables, analysis of variance