Difference between revisions of "SOCR EduMaterials AnalysisActivities ANOVA 1"

From SOCR
Jump to: navigation, search
m
(/* This SOCR Activity demonstrates the utilization of the SOCR Analyses package for statistical Computing. In particular, it shows how to use Analysis of Variance (ANOVA) and how to interpret the resu)
 
(8 intermediate revisions by 2 users not shown)
Line 3: Line 3:
 
== This SOCR Activity demonstrates the utilization of the SOCR Analyses package for statistical Computing. In particular, it shows how to use Analysis of Variance (ANOVA) and how to interpret the results ==
 
== This SOCR Activity demonstrates the utilization of the SOCR Analyses package for statistical Computing. In particular, it shows how to use Analysis of Variance (ANOVA) and how to interpret the results ==
  
* '''ANOVA Background''': Analysis of variance (ANOVA) is a class of statistical analysis models and  procedures, which compare means by splitting the overall observed variance into different parts. The initial techniques of the analysis of variance were pioneered by the statistician and geneticist R. A. Fisher in the 1920s and 1930s, and is sometimes known as Fisher's ANOVA or Fisher's analysis of variance, due to the use of Fisher's F-distribution as part of the test of statistical significance. [http://en.wikipedia.org/wiki/ANOVA | Read more about ANOVA].
+
* '''ANOVA Background''': Analysis of variance (ANOVA) is a class of statistical analysis models and  procedures, which compare means by splitting the overall observed variance into different parts. The initial techniques of the analysis of variance were pioneered by the statistician and geneticist R. A. Fisher in the 1920s and 1930s, and is sometimes known as Fisher's ANOVA or Fisher's analysis of variance, due to the use of Fisher's F-distribution as part of the test of statistical significance. [http://en.wikipedia.org/wiki/Simple_linear_regression Read more about ANOVA].
  
* '''SOCR ANOVA''': Go to SOCR [http://www.socr.ucla.edu/htmls/SOCR_Analyses.html Analyses]  and select the the 0ne-way ANOVA tab from the drop-down list of SOCR analyses, in the left panel. There are three ways to enter data in the SOCR ANOVA applet
+
* '''SOCR ANOVA''': Go to SOCR [http://www.socr.ucla.edu/htmls/SOCR_Analyses.html Analyses]  and select '''One-way ANOVA''' from the drop-down list of SOCR analyses, in the left panel. There are three ways to enter data in the SOCR ANOVA applet
** Click on the Example button on the top of the right panel.
+
** Click on the '''Example''' button on the top of the right panel.
** Generate Random data by clicking on the Random Example button
+
**Generate random data by clicking on the '''Random Example''' button
 
** Pasting your own data from a spreadsheet into SOCR ANOVA data table.  
 
** Pasting your own data from a spreadsheet into SOCR ANOVA data table.  
 
<center>[[Image:SOCR_AnalysisActivities_ANOVA_Dinov_011707_Fig1.jpg|400px]]</center>  
 
<center>[[Image:SOCR_AnalysisActivities_ANOVA_Dinov_011707_Fig1.jpg|400px]]</center>  
**Now, click the '''Raw Data''' check-box in the left panel, select '''Laplace Distribution''' (or any other distribution you want to sample from), choose the '''sample-size''' to be 100 (keep the center, Mu (<math>\mu=0</math>)) and click '''Sample'''. Then go to the '''Data''' tab, in the right panel. There you should see the 100 random Laplace observations stored as a column vector.
+
*Now, map the dependent and independent vartiables, by going to the '''Mapping''' tab, selecting columns from the available list and sending them to the corresponding bins on the right (see figure). Then press '''Calculate''' button to carry the ANOVA analysis.
** Next, go back to the '''Data Generation''' tab from the right panel and change the center of the Laplace distribution (set Mu=20, say). Click '''Sample''' again and you will see the list of randomly generated data in the '''Data''' tab expand to 200 (as you just sampled another set of 100 random Laplace observations).
+
<center>[[Image:SOCR_AnalysisActivities_ANOVA_Dinov_011707_Fig2.jpg|400px]]</center>  
 +
* The quantitative results results will be in the tab labeled '''Results'''. The '''Graphs''' tab contains the QQ Normal plot for the residuals. In this case, we have a very significant grouping effect, indicated by the p-value < <math>10^{-4}</math>.
 +
<center>[[Image:SOCR_AnalysisActivities_ANOVA_Dinov_011707_Fig4.jpg|400px]]</center>
  
  

Latest revision as of 15:42, 6 August 2007

SOCR Analysis Activities - SOCR Analysis of variance Activity

This SOCR Activity demonstrates the utilization of the SOCR Analyses package for statistical Computing. In particular, it shows how to use Analysis of Variance (ANOVA) and how to interpret the results

  • ANOVA Background: Analysis of variance (ANOVA) is a class of statistical analysis models and procedures, which compare means by splitting the overall observed variance into different parts. The initial techniques of the analysis of variance were pioneered by the statistician and geneticist R. A. Fisher in the 1920s and 1930s, and is sometimes known as Fisher's ANOVA or Fisher's analysis of variance, due to the use of Fisher's F-distribution as part of the test of statistical significance. Read more about ANOVA.
  • SOCR ANOVA: Go to SOCR Analyses and select One-way ANOVA from the drop-down list of SOCR analyses, in the left panel. There are three ways to enter data in the SOCR ANOVA applet
    • Click on the Example button on the top of the right panel.
    • Generate random data by clicking on the Random Example button
    • Pasting your own data from a spreadsheet into SOCR ANOVA data table.
SOCR AnalysisActivities ANOVA Dinov 011707 Fig1.jpg
  • Now, map the dependent and independent vartiables, by going to the Mapping tab, selecting columns from the available list and sending them to the corresponding bins on the right (see figure). Then press Calculate button to carry the ANOVA analysis.
SOCR AnalysisActivities ANOVA Dinov 011707 Fig2.jpg
  • The quantitative results results will be in the tab labeled Results. The Graphs tab contains the QQ Normal plot for the residuals. In this case, we have a very significant grouping effect, indicated by the p-value < \(10^{-4}\).
SOCR AnalysisActivities ANOVA Dinov 011707 Fig4.jpg






Translate this page:

(default)
Uk flag.gif

Deutsch
De flag.gif

Español
Es flag.gif

Français
Fr flag.gif

Italiano
It flag.gif

Português
Pt flag.gif

日本語
Jp flag.gif

България
Bg flag.gif

الامارات العربية المتحدة
Ae flag.gif

Suomi
Fi flag.gif

इस भाषा में
In flag.gif

Norge
No flag.png

한국어
Kr flag.gif

中文
Cn flag.gif

繁体中文
Cn flag.gif

Русский
Ru flag.gif

Nederlands
Nl flag.gif

Ελληνικά
Gr flag.gif

Hrvatska
Hr flag.gif

Česká republika
Cz flag.gif

Danmark
Dk flag.gif

Polska
Pl flag.png

România
Ro flag.png

Sverige
Se flag.gif