Chapter 1
Introduction
Learning Objectives (1 of 2)
Define biostatistical applications and their objectives
Explain the limitations of biostatistical analysis
Compare and contrast a population and a sample
Explain the importance of random sampling
Learning Objectives (2 of 2)
Develop research questions and select appropriate outcome variables to address important public health problems
Identify the general principles and explain the role and importance of biostatostistical analysis in medical, public health, and biological research
What Is Biostatistics? (1 of 2)
Application of statistical principles to medical, public health, and biological applications
Collecting, summarizing, and interpreting information and
Making inferences that appropriately account for uncertainty
What Is Biostatistics? (2 of 2)
Population
(unknown information)
Sample
Summarize sample
Make inferences about Population
Issues and Limitations (1 of 2)
Must clearly define research question
Must choose appropriate study design (i.e., the way in which data are collected)
Must select a sufficiently large, representative sample
Must carefully collect and summarize data
Issues and Limitations (2 of 2)
Must quantify uncertainty
Must appropriately account for relationships among characteristics
Must limit inferences to appropriate population
Important Questions
H1N1 outbreak
Risk factors for heart disease
Drug safety and efficacy
High-risk health behaviors
Genetic determinants of disease
Risk factors for autism
Impact of diet and exercise on health
Impact of Gulf oil spill on health
Issues for Biostatisticians (1 of 2)
Children: Obesity, immunizations, asthma, autism, etc.
Adolescents: Alcohol and tobacco use, depression, STDs, traffic accidents, etc.
Adults: Cancer, CVD, substance abuse, HIV/AIDS, mental health, etc.
What is number one killer of men and women in United States?
What are the risk factors?
Issues for Biostatisticians (2 of 2)
Research question
Study sample
Sample size
Analytic techniques
Inferences—cause/effect
Limitations
Types of Studies
Laboratory studies
Animal studies
Clinical studies
Observational studies
Experimental trials
Research Teams
Principal investigator
Biostatistician
Co-investigators
Project manager
Statistical programmers
Research assistants
Biostatistician’s Role on Team
Study design
Research question
Study sample
Sample size
Enrollment/follow-up strategies
Ongoing monitoring
Interim and final analysis
Reporting of results
Careers
Pharmaceutical industry
Government
Academia
Health insurance
Demand far exceeds supply of qualified biostatisticians today.
Training/Skills
Mathematics background
Biostatistics/statistics
Public health/biology
Computer skills
Communication skills
Analytic skills
Organizational skills
Attention to detail
