Those who complete this course will be able to select appropriate methods of multivariate data analysis, given multivariate data and study objectives; write SAS and/or Minitab programs to carry out multivariate data analyses; and interpret results of multivariate data analyses. Perfect for students and teachers wanting to learn/acquire materials for this topic.
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.
The program DistCalc calculates probabilities and critical values for the most important distributions. The purpose of this program is to show the concept of critical values and the replacement of printed distribution tables. The Distribution Calculator offers calculations for the normal distribution, the t distribution, the chi-square distribution, and the F distribution.
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.
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.
A song for use in helping students interpret the basics of regression including checking assumptions interpretation of slope, r, and r2. Lyric © 2015 Lawrence M. Lesser; Music by Dominic Dousa. This song is part of an NSF-funded library of interactive songs that involved students creating responses to prompts that are then included in the lyrics (see www.causeweb.org/smiles for the interactive version of the song, a short reading covering the topic, and an assessment item).
A song to teach about the relationship between the slope of the regression line and the correlation. The lyric was authored by Lawrence Mark Lesser from the University of Texas at El Paso. The song may be sung to the tune of the English lullaby "Twinkle Twinkle Little Star" (Jane Taylor, 1806). Free for use in non-commercial teaching. This song is also part of an NSF-funded library of interactive songs that involved students creating responses to prompts that are then included in the lyrics (see www.causeweb.org/smiles for the interactive version of the song, a short reading covering the topic, and an assessment item).
These cheat sheets make it easy to learn about and use some of the favorite packages of RStudio.
This applet allows a person to add up to 50 points onto its green viewing screen. After each point is added by clicking on the screen with the mouse, a red line will appear. This red line represents a line passing through (Average x, Average y) with a slope that can be altered by clicking the Left or Right buttons. The slope of this line may also be changed by dragging the mouse either right or left. By clicking on Show Best Fit, a blue best fit line will be calculated by the computer.
This is a "Building Block" for the Buffon Needle problem. The source code and compile code are included as well as separate files for each. Users able to test the applet to determine if it meets their needs.