This *advanced* level data set has 704 rows and 21 columns.
This *advanced* level data set has Autistic Spectrum Disorder (ASD) Screening Test Data for 704 adults. There are 21 attributes in the dataset that include test takers'
The data set contains Autistic Spectrum Disorder Screening Data for Adult. This dataset can be used for classification and predictive tasks.
demographics such as *Age*, *Gender*, *Ethnicity* etc. The screening test included 10 questions (A1 to A10) that test takers answered. In each of these 10 questions,
the test takers were given a statement with which they had to agree or disagree. For example, the statement at question A1 is "I often notice small sounds when other do not".
The test takers' responses to A1 and A10 are coded as binary values (0,1). Once the test taker has answered all 10 questions, his/her status on ASD is determined which
is recorded under **Class/ASD** variable. You can encouraged to explore the [ASD Test Mobile App](http://asdtests.com/#)
This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, and **classification modelling techniques**.
This data set is recommended for learning and practicing your skills in **exploratory data analysis**, **data visualization**, and **classification modelling techniques**.
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This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Autism Screening Adult Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Autism+Screening+Adult).
This data set has been sourced from the Machine Learning Repository of University of California, Irvine [Autism Screening Adult Data Set (UC Irvine)](https://archive.ics.uci.edu/ml/datasets/Autism+Screening+Adult).
The UCI page mentions the following as the original source of the data set:
The UCI page mentions the following as the original source of the data set:
*Fadi Fayez Thabtah, Department of Digital Technology, Manukau Institute of Technology, Auckland, New Zealand*
+ Fadi Fayez Thabtah, Department of Digital Technology, Manukau Institute of Technology, Auckland, New Zealand