Event Title

The Big and Small Of It: Using Large Scale Social Data and Small Scale Rna-Seq Data

Location

Hager-Lubbers Exhibition Hall

Start Date

18-4-2017 3:30 PM

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.

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Apr 18th, 3:30 PM

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.