Event Title
The Big and Small Of It: Using Large Scale Social Data and Small Scale Rna-Seq Data
Location
Hager-Lubbers Exhibition Hall
Description
PURPOSE: To fulfill the requirements to receive an MS in Biostatistics at Grand Valley State University all students must complete a 440-hour internship. To help satisfy this requirement I completed two separate 400+ hour internships, one at the Ottawa County Department of Public Health, the other at Van Andel Research Institute. CHALLENGE: At each internship, I had to use large scale social data or small scale RNA-seq data. These required separate statistical techniques and research was conducted on how to best apply differing processes. EXPERIENCE: The goals of these internships were to further my skills as a biostatistician. I was expected to analyze data sets, clean data, produce results, write reports, and convey my findings, all while using a statistical programming package such as SAS or R. OUTCOME: Through both internships, I was able to meet all of the expected objectives while increasing my knowledge of statistics, data mining, and statistical programming. IMPACT: The data I analyzed is now being used by local entities to develop programs for youth living in Ottawa County and the data mining techniques helped to form new hypotheses’ at VARI.
The Big and Small Of It: Using Large Scale Social Data and Small Scale Rna-Seq Data
Hager-Lubbers Exhibition Hall
PURPOSE: To fulfill the requirements to receive an MS in Biostatistics at Grand Valley State University all students must complete a 440-hour internship. To help satisfy this requirement I completed two separate 400+ hour internships, one at the Ottawa County Department of Public Health, the other at Van Andel Research Institute. CHALLENGE: At each internship, I had to use large scale social data or small scale RNA-seq data. These required separate statistical techniques and research was conducted on how to best apply differing processes. EXPERIENCE: The goals of these internships were to further my skills as a biostatistician. I was expected to analyze data sets, clean data, produce results, write reports, and convey my findings, all while using a statistical programming package such as SAS or R. OUTCOME: Through both internships, I was able to meet all of the expected objectives while increasing my knowledge of statistics, data mining, and statistical programming. IMPACT: The data I analyzed is now being used by local entities to develop programs for youth living in Ottawa County and the data mining techniques helped to form new hypotheses’ at VARI.