SOCR Data

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=== Biomedical Data===
=== Biomedical Data===
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* [[SOCR_Data_PD_BiomedBigMetadata|Human Health: Predictive Big Data Analytics, Modeling and Visualization of Clinical, Genetic and Imaging Data for Parkinson’s Disease]]
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* [[SOCR_Data_AMI_NY_1993_HeartAttacks| 1993 New York State Heart Attack Patients: Acute Myocardial Infarction (AMI), N=12,844]]
* [[SOCR_Data_AD_BiomedBigMetadata|Human Health: Modeling and Analysis of Clinical, Genetic and Imaging Data of Alzheimer’s Disease]]
* [[SOCR_Data_AD_BiomedBigMetadata|Human Health: Modeling and Analysis of Clinical, Genetic and Imaging Data of Alzheimer’s Disease]]
* [[SOCR_Data_Dinov_032708_AllometricPlanRels | Allometric  relationship between population density, body mass and metabolic activity in Plants]]
* [[SOCR_Data_Dinov_032708_AllometricPlanRels | Allometric  relationship between population density, body mass and metabolic activity in Plants]]
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* [[SOCR_Data_KneePainData_041409 | Knee Pain Centroid Locations Data]]
* [[SOCR_Data_KneePainData_041409 | Knee Pain Centroid Locations Data]]
* [[SOCR_Data_NIPS_InfantVitK_ShotData | Neonate Infant Pain Score (NIPS) Data (Vitamin K shots)]]
* [[SOCR_Data_NIPS_InfantVitK_ShotData | Neonate Infant Pain Score (NIPS) Data (Vitamin K shots)]]
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===Healthcare and Health Science Data===
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* [https://umich.instructure.com/courses/38100/files/ A number of case-studies including Big and Heterogeneous clinical, nursing, and healthcare datasets].
=== [[SOCR_US_CensusData | US Census Data]]===
=== [[SOCR_US_CensusData | US Census Data]]===
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* [[SOCR_061708_NC_Data_Aquifer | Texas Wolfcamp aquifer data]]
* [[SOCR_061708_NC_Data_Aquifer | Texas Wolfcamp aquifer data]]
* [[SOCR_012708_ID_Data_HotDogs | Hot Dog Calorie and Sodium Dataset]]
* [[SOCR_012708_ID_Data_HotDogs | Hot Dog Calorie and Sodium Dataset]]
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* [http://search.datacite.org/ui DataCite DOI Archive for diverse types of datasets]
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==Machine Interfaces to Downloading [[SOCR Data]]==
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In addition to human interactions with the [[SOCR Data]], we provide several machine interfaces to consume and process these data.
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* [[SOCR Data]] can be copy pasted directly from the Wiki HTML pages into any of the [http://socr.umich.edu/html/ana/ SOCR Java applets].
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* SOCR Data can also be loaded into an R computational environment automatically using the protocol below illustrated with the case of a [[SOCR_Data_PD_BiomedBigMetadata|Parkinson's Disease dataset]]:
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library(rvest)
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# Loading required package: xml2
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wiki_url <- read_html("http://wiki.socr.umich.edu/index.php/SOCR_Data_PD_BiomedBigMetadata")
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html_nodes(wiki_url, "#content")
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pd_data <- html_table(html_nodes(wiki_url,"table")<math>[[1]]</math>)
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head(pd_data); summary(pd_data)
<hr>
<hr>

Revision as of 16:35, 9 May 2016

Contents

SOCR Educational Materials - SOCR Data

The links below contain a number of datasets that may be used for demonstration purposes in probability and statistics education. There are two types of data - simulated (computer-generated using random sampling) and observed (research, observationally or experimentally acquired).

SOCR Data

Simulated data

The SOCR resources provide a number of mechanisms to simulate data using computer random-number generators. Here are some of the most commonly used SOCR generators of simulated data:

Observed data

The following collections include a number of real observed datasets from different disciplines, acquired using different techniques and applicable in different situations.

Climate Change Data

Population Data

Economic, Business and Stock Market Data

Consumer Price Index (CPI)

Stock Market Data

Monetary-Base Data

Budgets and Deficits Data

Sector Data, Population Perception Trends data

World Peace

Neuroimaging Data

Biomedical Data

Healthcare and Health Science Data

US Census Data

US Elections Data

Other Data

Machine Interfaces to Downloading SOCR Data

In addition to human interactions with the SOCR Data, we provide several machine interfaces to consume and process these data.

  • SOCR Data can be copy pasted directly from the Wiki HTML pages into any of the SOCR Java applets.
  • SOCR Data can also be loaded into an R computational environment automatically using the protocol below illustrated with the case of a Parkinson's Disease dataset:
library(rvest)
# Loading required package: xml2

wiki_url <- read_html("http://wiki.socr.umich.edu/index.php/SOCR_Data_PD_BiomedBigMetadata")
html_nodes(wiki_url, "#content")

pd_data <- html_table(html_nodes(wiki_url,"table")[[1]])
head(pd_data); summary(pd_data)



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