SOCR ResamplingSimulation Activity - Revision history

IvoDinov: /* Learning Activity */

2013-04-10T22:17:47Z

‎Learning Activity

IvoDinov: /* Learning Activity */

2013-04-10T22:17:15Z

‎Learning Activity

IvoDinov at 22:15, 10 April 2013

2013-04-10T22:15:57Z

IvoDinov at 22:09, 10 April 2013

2013-04-10T22:09:09Z

IvoDinov at 22:03, 10 April 2013

2013-04-10T22:03:57Z

IvoDinov: added videos section

2012-10-11T16:12:17Z

added videos section

IvoDinov: /* Requirements & usability */

2012-10-10T17:38:01Z

‎Requirements & usability

IvoDinov at 17:37, 10 October 2012

2012-10-10T17:37:09Z

IvoDinov at 19:48, 3 August 2012

2012-08-03T19:48:43Z

IvoDinov: Created page with '== SOCR Educational Materials - Activities - SOCR Resampling, Randomization and Simulation Activity == This activity illustrates the processes…'

2012-08-03T19:37:55Z

Created page with '== SOCR Educational Materials - Activities - SOCR Resampling, Randomization and Simulation Activity == This activity illustrates the processes…'

New page

== [[SOCR_EduMaterials_Activities | SOCR Educational Materials - Activities]] - SOCR Resampling, Randomization and Simulation Activity ==

This activity illustrates the processes of sampling, resampling, similation and randomization using the SOCR [http://socr.ucla.edu/htmls/HTML5/ResamplingSimulation/ Resampling, Randomization and Simulation Webapp]. It is implemented in HTML5/JavaScript and should be portable on any computer, operating system and web-browser.

==Goals==
The aims of this activity are to:
* ...

==Background==
TBD ...

==Requirements & usability==
A modern web-browser with HTML and JavaScript support is required (mobile devices should be fine).
# Go to the [http://socr.ucla.edu/htmls/HTML5/ResamplingSimulation/ SOCR resampling/simulation webapp].
# ...

==Learning Activity: TBD==
TBD ...

==Practice experiments==
TBD ...

==References==
* Dinov, ID, Christou, N and Sanchez, J. (2008) [http://www.amstat.org/publications/jse/v16n2/dinov.html Central Limit Theorem: New SOCR Applet and Demonstration Activity], [http://www.amstat.org/publications/jse/ Journal of Statistics Education], Volume 16, Number 2.

{{translate|pageName=http://wiki.stat.ucla.edu/socr/index.php?title=SOCR_ResamplingSimulation_Activity}}

@@ Line 43: / Line 43: @@
 # Back at the Webapp startup screen select the “Use Excel Datasheet” Option
 # Click the “Reset” button to remove any previous data from the webapp buffer.
-# Copy-paste data from any data-table, For instance from this Heights/Weights dataset: http://wiki.stat.ucla.edu/socr/index.php/SOCR_Data_Dinov_020108_HeightsWeights
+# Copy-paste data from any data-table, For instance from this [[SOCR_Data_Dinov_020108_HeightsWeights|Heights/Weights dataset]].
 # Let’s select a set of say 20 Weights and click “Use Selected” (this would represent sample 1). Repeat this selection with another set of 20 Weights.
 # Click “Proceed”. You should see a summary indicating the sample-sizes of the 2 groups of data you selected

@@ Line 30: / Line 30: @@
 * You can either generate random data or copy-paste in your own data. For instance you can generate data using coins/cards, etc., or use one of the [[SOCR_Data|SOCR datasets]] (e.g., [[SOCR_Data_Dinov_020108_HeightsWeights| Human Heights/Weights]])
 * Simulation-Driven Randomization Inference:
-## To use the Coin-Toss experiment to generate data, click “''Binomial Coin Toss''”
+# To use the Coin-Toss experiment to generate data, click “''Binomial Coin Toss''”
-## Choose the parameters -- number of coins, probability of Heads, and number of samples (e.g., k=2)
+# Choose the parameters -- number of coins, probability of Heads, and number of samples (e.g., k=2)
-## Click “''Generate Dataset''“ (you can click this button multiple times, notice how the data samples change)
+# Click “''Generate Dataset''“ (you can click this button multiple times, notice how the data samples change)
-## Click “''Generate Ransom Samples''”
+# Click “''Generate Ransom Samples''”
-## Select sample sizes (e.g., 10) and number of repeated samples (e.g., 10,000)
+# Select sample sizes (e.g., 10) and number of repeated samples (e.g., 10,000)
-## Click the “RUN” button
+# Click the “RUN” button
-## You can inspect all samples (for the k=2 groups) in the right panel of the webapp (use “Show” button and inspect all the glyphs on the top)
+# You can inspect all samples (for the k=2 groups) in the right panel of the webapp (use “Show” button and inspect all the glyphs on the top)
-## Then select “Test Statistics”, e.g., p-value, and Click “Infer” button
+# Then select “Test Statistics”, e.g., p-value, and Click “Infer” button
-## This will automatically open you the “Inference Plot” tab where the randomization distribution (of p-values) is shown and the initial p_o value is drawn on top to show the relation to the resampling-based distribution.
+# This will automatically open you the “Inference Plot” tab where the randomization distribution (of p-values) is shown and the initial p_o value is drawn on top to show the relation to the resampling-based distribution.
-## You can always make modifications of your prior choices in the “Control” tab.
+# You can always make modifications of your prior choices in the “Control” tab.
 * Data-Driven Randomization Inference:
-## Back at the Webapp startup screen select the “Use Excel Datasheet” Option
+# Back at the Webapp startup screen select the “Use Excel Datasheet” Option
-## Click the “Reset” button to remove any previous data from the webapp buffer.
+# Click the “Reset” button to remove any previous data from the webapp buffer.
-## Copy-paste data from any data-table, For instance from this Heights/Weights dataset: http://wiki.stat.ucla.edu/socr/index.php/SOCR_Data_Dinov_020108_HeightsWeights
+# Copy-paste data from any data-table, For instance from this Heights/Weights dataset: http://wiki.stat.ucla.edu/socr/index.php/SOCR_Data_Dinov_020108_HeightsWeights
-## Let’s select a set of say 20 Weights and click “Use Selected” (this would represent sample 1). Repeat this selection with another set of 20 Weights.
+# Let’s select a set of say 20 Weights and click “Use Selected” (this would represent sample 1). Repeat this selection with another set of 20 Weights.
-## Click “Proceed”. You should see a summary indicating the sample-sizes of the 2 groups of data you selected
+# Click “Proceed”. You should see a summary indicating the sample-sizes of the 2 groups of data you selected
-## Click “Done” – this will open the “Control” panel
+# Click “Done” – this will open the “Control” panel
-## Select sample sizes (e.g., 10) and number of repeated samples (e.g., 10,000)
+# Select sample sizes (e.g., 10) and number of repeated samples (e.g., 10,000)
-## Click the “RUN” button
+# Click the “RUN” button
-## You can inspect all samples (for the k=2 groups) in the right panel of the webapp (use “Show” button and inspect all the glyphs on the top)
+# You can inspect all samples (for the k=2 groups) in the right panel of the webapp (use “Show” button and inspect all the glyphs on the top)
-## Then select “Test Statistics”, e.g., p-value, and Click “Infer” button
+# Then select “Test Statistics”, e.g., p-value, and Click “Infer” button
-## This will automatically open you the “Inference Plot” tab where the randomization distribution (of p-values) is shown and the initial p_o value is drawn on top to show the relation to the resampling-based distribution.
+# This will automatically open you the “Inference Plot” tab where the randomization distribution (of p-values) is shown and the initial p_o value is drawn on top to show the relation to the resampling-based distribution.
-## You can always make modifications of your prior choices in the “Control” tab.
+# You can always make modifications of your prior choices in the “Control” tab.
 * Some new features (e.g., data import from WorldBank and other URLs) will be added it the next 2 weeks

@@ Line 2: / Line 2: @@
 This activity illustrates the processes of sampling, resampling, similation and randomization using the SOCR [http://socr.ucla.edu/htmls/HTML5/SOCR_Resampling_Webapp/ Resampling, Randomization and Simulation Webapp]. It is implemented in HTML5/JavaScript and should be portable on any computer, operating system and web-browser.
 ==Goals==
@@ Line 18: / Line 19: @@
 # Test the webapp
 # [https://github.com/SOCRedu/Resampling-Randomization-WebApp Report any constructive and critical feedback]
 ==Learning Activity==

@@ Line 11: / Line 11: @@
 ==Background==
-TBD ...
+Random (re)sampling applies stochasticity or randomness in the sampling scheme and reflects what is sampled and what the distribution we sample from is. In [[EBook#Chapter_VIII:_Hypothesis_Testing|parametric-based statistical inference]], the random sampling reflects the stochastic nature of selecting observations from the sample space. In contrast, in randomization-based inference (e.g., bootstrapping), the random sampling reflects the resampling and stochastic assignment of units to treatments or groups.
 ==Requirements & usability==
 A modern web-browser with enabled HTML and JavaScript support is required (mobile devices, tablets and phones should work fine).
-# Go to the [http://socr.ucla.edu/htmls/HTML5/SOCR_Resampling_Webapp/ SOCR Sesampling/Simulation Webapp].
+# Go to the [http://socr.ucla.edu/htmls/HTML5/SOCR_Resampling_Webapp/ SOCR Resampling/Simulation Webapp].
 # Test the webapp
 # [https://github.com/SOCRedu/Resampling-Randomization-WebApp Report any constructive and critical feedback]
@@ Line 24: / Line 24: @@
 You can perform single sample or multiple sample based statistical inference using this resource. Let's take a 2-sample case as a specific example where we are looking for group differences. Follow this protocol to get some simulations/results (both for teaching/learning randomization-based inference, or do do real data analysis):
-# You can either generate random data or copy-paste in your own data. For instance you can generate data using coins/cards, etc., or use one of the [[SOCR_Data|SOCR datasets]] (e.g., [[SOCR_Data_Dinov_020108_HeightsWeights| Human Heights/Weights]])
+* You can either generate random data or copy-paste in your own data. For instance you can generate data using coins/cards, etc., or use one of the [[SOCR_Data|SOCR datasets]] (e.g., [[SOCR_Data_Dinov_020108_HeightsWeights| Human Heights/Weights]])
-# Simulation-Driven Randomization Inference:
+* Simulation-Driven Randomization Inference:
 ## To use the Coin-Toss experiment to generate data, click “''Binomial Coin Toss''”
 ## Choose the parameters -- number of coins, probability of Heads, and number of samples (e.g., k=2)
@@ Line 36: / Line 36: @@
 ## This will automatically open you the “Inference Plot” tab where the randomization distribution (of p-values) is shown and the initial p_o value is drawn on top to show the relation to the resampling-based distribution.
 ## You can always make modifications of your prior choices in the “Control” tab.
-# Data-Driven Randomization Inference:
+* Data-Driven Randomization Inference:
 ## Back at the Webapp startup screen select the “Use Excel Datasheet” Option
 ## Click the “Reset” button to remove any previous data from the webapp buffer.
@@ Line 49: / Line 49: @@
 ## This will automatically open you the “Inference Plot” tab where the randomization distribution (of p-values) is shown and the initial p_o value is drawn on top to show the relation to the resampling-based distribution.
 ## You can always make modifications of your prior choices in the “Control” tab.
-# Some new features (e.g., data import from WorldBank and other URLs) will be added it the next 2 weeks
+* Some new features (e.g., data import from WorldBank and other URLs) will be added it the next 2 weeks
 ==Practice experiments==

@@ Line 5: / Line 5: @@
 ==Goals==
 The aims of this activity are to:
-* ...
+* Demonstrate the concepts of simulation and data generation
 ==Background==
@@ Line 11: / Line 14: @@
 ==Requirements & usability==
-A modern web-browser with HTML and JavaScript support is required (mobile devices should be fine).
+A modern web-browser with enabled HTML and JavaScript support is required (mobile devices, tablets and phones should work fine).
 # Go to the [http://socr.ucla.edu/htmls/HTML5/SOCR_Resampling_Webapp/ SOCR Sesampling/Simulation Webapp].
-# ...
+# Test the webapp
-==Learning Activity: TBD==
+==Learning Activity==
-TBD ...
+Load the [http://socr.ucla.edu/htmls/HTML5/SOCR_Resampling_Webapp/ SOCR resampling and randomization webapp] in your browser.
 ==Practice experiments==
-TBD ...
+Repeat the protocol above with different (observed or simulated) data, different study designs (e.g., single sample, vs. multiple samples, etc.)
 ==Videos==

@@ Line 20: / Line 20: @@
 ==Practice experiments==
 TBD ...
 ==See also==

@@ Line 1: / Line 1: @@
 == [[SOCR_EduMaterials_Activities | SOCR Educational Materials - Activities]] - SOCR Resampling, Randomization and Simulation Activity ==
-This activity illustrates the processes of sampling, resampling, similation and randomization using the SOCR [http://socr.ucla.edu/htmls/HTML5/ResamplingSimulation/ Resampling, Randomization and Simulation Webapp]. It is implemented in HTML5/JavaScript and should be portable on any computer, operating system and web-browser.
+This activity illustrates the processes of sampling, resampling, similation and randomization using the SOCR [http://socr.ucla.edu/htmls/HTML5/SOCR_Resampling_Webapp/ Resampling, Randomization and Simulation Webapp]. It is implemented in HTML5/JavaScript and should be portable on any computer, operating system and web-browser.
 ==Goals==
@@ Line 23: / Line 23: @@
 ==See also==
 * [[SOCR_Resampling_HTML5_Project|SOCR Resampling and Simulation HTML5 Project page]]
 ==References==