Difference between revisions of "SOCR EduMaterials AnalysisActivities MLR"
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* Generate random data by clicking on the '''Random Example''' button. | * Generate random data by clicking on the '''Random Example''' button. | ||
* Paste your own data from a spreadsheet into SOCR Multiple Linear Regression data table. | * Paste your own data from a spreadsheet into SOCR Multiple Linear Regression data table. | ||
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| + | ==SOCR Multiple Linear Regression Example== | ||
| + | We will demonstrate Multiple Linear Regression with some SOCR built-in example. This example is based on a dataset from the statistical program "R." For more information of the R program, please see [http://cran.r-project.org/ CRAN Home Page]. The dataset used here is "hills" under R's "MASS" library. The dataset describe the record times in 1984 for 35 Scottish hill races. There are three variables: '''dist''' for distance in miles, '''climb''' total height gained during the route, in feet, and '''time''' record time in minutes. | ||
Revision as of 23:34, 4 August 2007
Contents
SOCR Analysis Example on Multiple Linear Regression
This SOCR Activity demonstrates the utilization of the SOCR Analyses package for statistical Computing. In particular, it shows how to use Multiple Linear Regression and how to read the output results.
Multiple Linear Regression Background
Multiple Linear Regression is a class of statistical analysis models and procedures, which takes one independent variable and one dependent and one or more variable, both sets being quantitative, and models the relationship between them. SOCR has another activity set for Simple Linear Regression, which only allows on independent variable in the input. However, SOCR Multiple Linear Regression allows one or more independent variables. In the linear model, the error is assumed to follow a standard normal distribution.
The goal of the Multiple Linear Regression computing procedure is to estimate all of the coefficients based on the data. Least Squares Fitting is used.
In this activity, the students can learn about:
- Reading results of Simple Linear Regression;
- Making interpretation of the coefficients;
- Observing and interpreting various data and resulting plots
- Scatter plots of the dependent vs. independent variables
- Diagnostic plots such as the Residual on Fit plot
- Normal QQ plot, etc.
SOCR Multiple Linear Regression Data Input
Go to SOCR Analyses and select Multiple Linear Regression from the drop-down list of SOCR analyses, in the left panel. There are three ways to enter data in the SOCR Multiple Linear Regression applet:
- Click on the Example button on the top of the right panel.
- Generate random data by clicking on the Random Example button.
- Paste your own data from a spreadsheet into SOCR Multiple Linear Regression data table.
SOCR Multiple Linear Regression Example
We will demonstrate Multiple Linear Regression with some SOCR built-in example. This example is based on a dataset from the statistical program "R." For more information of the R program, please see CRAN Home Page. The dataset used here is "hills" under R's "MASS" library. The dataset describe the record times in 1984 for 35 Scottish hill races. There are three variables: dist for distance in miles, climb total height gained during the route, in feet, and time record time in minutes.
