SAS programmer analyst
Resume:
CHUNLEI ZHANG
Home address:
San Mateo, CA 94403
QUALIFICATIONS
▪ Experienced user of SAS in Qualification; Certified Base Programmer for SAS®9
▪ Competent with multiple linear and logistic regression, Cox model, GLM
▪ Thoroughly proficient in data management and data manipulation in SAS
▪ Excellent training in statistical methods such as design of experiment, descriptive statistics graphical methods,
hypothesis testing , C.I.s, categorical data analysis, ANOVA, survival analysis, and sample size and power computation
for various statistical settings
▪ Extensive and integrated knowledge in clinical trials, epidemiology and public health
▪ Outstanding communication and interpersonal skills, quick learner, self-motivated and detail-oriented
EDUCATION
▪ M.S. in Department of Statistics and Biostatistics, California State University-East Bay June 2010
COURSEWORK
▪ Probability Theory ▪ Advanced Statistical Inference ▪ Statistical Theory
▪ Analysis of Variance Models▪ Statistical Programming (SAS)
▪ Theory and Application of Regression ▪ Advanced Probability ▪ Categorical Data Analysis
▪ Survival Analysis ▪ Mathematical Statistics I ▪ Mathematical Statistics II ▪ Clinical Trials
COMPUTER SKILLS
▪ SAS®Certified Base Programmer for SAS®9
▪ SAS/Stat/Graph/Macro/SQL
▪ Minitab, SPSS, R, Matlab
▪ Microsoft Excel, Word, Access and PowerPoint
PROFESSIONAL EXPERIENCE
▪ Teaching Assistant, Department of Statistics, California State University-East Bay 09/2009 ~ 06/2010
Course: Elements of Probability and Statistics (evaluate students’ assignments and exams)
AFFILIATION
▪ Member of American Statistical Association
▪ Member of Institute of Mathematical Statistics
SELECTED COURSE PROJECTS
Time Required to Stabilize Tests under 5 simulated emergency
conditions using each of 3 prototype display panels
Department of Statistics and Biostatistics, California State University, East Bay Spring, 2009
▪ Identified the main risk factors and Conducted Two-Factor ANOVA Model with interaction term and profile analysis to
test the difference between two groups
Study about if the grades are predictive of the scores
Department of Statistics and Biostatistics, California State University, East Bay Fall, 2009
▪ Two teachers think that their grades are predictive of the scores students receive on a certain standardized exam. The
goal is compare the grades and the scores that 48 students were given on the exam
▪ Fit the linear regression model and give the resulting least squares line and interpret the terms
▪ Give and interpret the joint 95% confidence interval for β0, β1 and β2 in the model
▪ Give the plots associated with the test of normality, the test of constant variance
Study of prostate cancer patients receiving surgery
Department of Statistics and Biostatistics, California State University, East Bay Spring, 2010
▪ Explored a clinical data set that have been collected from 53 prostate cancer patients receiving surgery, to determine
which of 5 preoperative variables (Age, Acid, Grade, Stage, X-ray) are predictive of nodal involvement
▪ Recommended logistic regression models to analyze this data
▪ Model selection was performed by PROC LOGISTIC using the Backward elimination
▪ Explained results adequately by integrating statistical results
REFERENCES
Available upon request
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