Data Analysis

Qiong Jia Email: ***********@*****.*** ********@***.*** Tel: 213-***-**** Los Angeles, CA

SUMMARY

Master solid knowledge of biostatics and statistic dataset package; High proficiency in SAS and SPSS; 3+ years of experience in biostatics data analysis with SPSS; 1+ years of health care and clinical trial data analysis with SAS EDUCATION BACKGROUND

01/2015-12/2016 University of Southern California Degree: Master of Science Major: Biomedical Engineering 09/2010-07/2014 China Agricultural University Major: Biological Science Degree: Bachelor of Science CERTIFICATION

10/12/2016 SAS Advanced Programming for SAS 9 Grade 97% Accessing Data Using SQL 100%; Macro Processing 100%; Advanced Programming Techniques 90% 11/10/2016 SAS Based Programming for SAS 9 Grade 95% Accessing Data 90%; Creating Data Structures 100%; Generating Reports 100%; Handling Errors 100%; Managing Data 92%

SKILLS

l Biostatistics analysis software: SAS, SPSS

SAS:single and multiple linear regression analysis, logistic regression, correlation analysis, interaction and confounders evaluation, outliers evaluation, model selection (all possible subjects, forward, backward and stepwise methods), ANOVA, ANCOVA, proportion analysis, SQL

SPSS:z-test, t-test, non-parametric tests (Wilcoxon sighed rank test, Wilcoxon rank sum test), proportion test, correlation and regression analysis, variance analysis

l MATLAB: data analysis and regression (CFTOOL.etc) WORKING EXPERIENCE

Internship Institute of Grassland Research of CAAS (Chinese Academy of Agricultural Sciences) 06/2016-08/2016 Genetic Diversity Analysis in Avena Sativa L and E sibiricus Position: Data Analyst and Research Assistant

l Determined the smallest sample size to represent the genetic diversity of whole population to reduce cost and workload in further research process

Extracted genetic diversity information with SSR molecular marker; Run simple random sampling without replacement through SAS SURVEYSELECT process and MATLAB; Analyze genetic diversity information with Popgene32. Analyzed the relationship between sample size and genetic diversity index with SAS and MATLAB separately including based data summary statistics analysis, model regression prediction and outliers evaluation; l Explored relationship between the degree of aging and genetic diversity of whole population Model natural aging process with high temperature to extracted the genetic diversity information by SSR molecular marker; Analyzed the relationship between degree of aging and genetic diversity index separately by SAS and MATLAB PROJECTS

l Analysis the Relationship between Basic Factors (Age, BMI, Smoking History.etc) and Systolic Blood Pressure (SBP) Explored dataset; Analyzed preliminary relationship by PROC TTEST (between BMI, smoking history and SBP); Processed simple liner regression; Model selection; Residual and potential outliers analysis l Children’s Health Study of Lung function

Estimated the relationship between children’s lung function and basic factors; Model selection: explored connection between breathing air pollution and long-term health effects in children l Louisiana Cholesterol Data Analysis

Reported summary statistics of basic variables (later mentioned); Analyzed the relationship between serum lipid level in subjects (Triglycerides, Cholesterol and high density lipids) and some basic subject index (age, sex, BMI, height, weight, smoke, alcohol) (multiple liner regression, ANOVA, ANCOVA, logistic regression); Model selection; Residual and potential outliers analysis

COURSES

USC: Principles of biostatistics, Data analysis,

Advanced topics in biomedical systems, Advanced studies of the Neuro System CAU: Bioinformatics, Biostatistics

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