Biostatistics

Introduction to Biostatistics

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Source: Johns Hopkins Bloomberg School of Public Health

Type: PowerPoint & Lecture Materials

Level: Basic

Description: Introduction to Biostatistics provides an introduction to selected important topics in biostatistical concepts and reasoning. This course represents an introduction to the field and provides a survey of data and data types. Specific topics include tools for describing central tendency and variability in data; methods for performing inference on population means and proportions via sample data; statistical hypothesis testing and its application to group comparisons; issues of power and sample size in study designs; and random sample and other study types. While there are some formulae and computational elements to the course, the emphasis is on interpretation and concepts.

Continuing Education Credits: N/A



Biostatistical Methodology in Clinical Trials

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Source: ClinDescience Consultancy for Drug and Clinical Development

Type: Article

Level: Basic

Description: This article reviews types of clinical trials and sampling strategies.

Continuing Education Credits: N/A



Methods in Biostatistics 1

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Source: Johns Hopkins Bloomberg School of Public Health

Type: PowerPoint & Lecture Materials

Level: Basic

Description: Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations.

Continuing Education Credits: N/A



Methods in Biostatistics 2

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Source: Johns Hopkins Bloomberg School of Public Health

Type: PowerPoint & Lecture Materials

Level: Intermediate

Description: Presents fundamental concepts in applied probability, exploratory data analysis, and statistical inference, focusing on probability and analysis of one and two samples. Topics include discrete and continuous probability models; expectation and variance; central limit theorem; inference, including hypothesis testing and confidence for means, proportions, and counts; maximum likelihood estimation; sample size determinations; elementary non-parametric methods; graphical displays; and data transformations.

Continuing Education Credits: N/A

 



Statistical Reasoning 1

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Source: Johns Hopkins Bloomberg School of Public Health

Type: PowerPoint & Lecture Materials

Level: Basic

Description: Statistical Reasoning in Public Health I provides a broad overview of biostatistical methods and concepts used in the public health sciences, emphasizing interpretation and concepts rather than calculations or mathematical details. It develops ability to read the scientific literature to critically evaluate study designs and methods of data analysis, and it introduces basic concepts of statistical inference, including hypothesis testing, p-values, and confidence intervals. Topics include comparisons of means and proportions; the normal distribution; regression and correlation; confounding; concepts of study design, including randomization, sample size, and power considerations; logistic regression; and an overview of some methods in survival analysis. The course draws examples of the use and abuse of statistical methods from the current biomedical literature.

Continuing Education Credits: N/A



Statistical Reasoning 2

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Source: Johns Hopkins Bloomberg School of Public Health

Type: PowerPoint & Lecture Materials

Level: Intermediate

Description: Statistical Reasoning in Public Health II provides a broad overview of biostatistical methods and concepts used in the public health sciences, emphasizing interpretation and concepts rather than calculations or mathematical details. It develops ability to read the scientific literature to critically evaluate study designs and methods of data analysis. It introduces basic concepts of statistical inference, including hypothesis testing, p-values, and confidence intervals. Topics include comparisons of means and proportions; the normal distribution; regression and correlation; confounding; concepts of study design, including randomization, sample size, and power considerations; logistic regression; and an overview of some methods in survival analysis. The course draws examples of the use and abuse of statistical methods from the current biomedical literature.

Continuing Education Credits: N/A



Quick Health Data Online

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Source: The Office On Women’s Health at the US Department of Health and Human Services

Type: Online database

Level: Basic

Description: This database provides information and statistics on many health topics. Users can search for data by selecting from the following categories: access, codes and status, demographics, disease, maternal health, mental health, mortality, prevention, reproductive health, violence, and HP 2020; and selecting geographical areas to generate a report.



CER Online Learning Center

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Source: Center for Health Outcomes, Policy, and Evaluation Studies at The Ohio State University College of Public Health

Type: Modules

Level: Intermediate

Description: The modules on this webpage address a variety of topics related to the field of Comparative Effectiveness Research. In each module, examples of analysis methods are presented in a format that allows participants to understand their application and to work through them using their own analysis program.

 



Epi Info

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Source: Centers for Disease Control and Prevention

Type: Statistical Program

Level: Intermediate

Description: This a free statistics database and analysis software program from CDC.gov. “Physicians, nurses, epidemiologists, and other public health workers lacking a background in information technology often have a need for simple tools that allow the rapid creation of data collection instruments and data analysis, visualization, and reporting using epidemiologic methods. Epi Info™, a suite of lightweight software tools, delivers core ad-hoc epidemiologic functionality without the complexity or expense of large, enterprise applications.

Epi Info™ is easily used in places with limited network connectivity or limited resources for commercial software and professional IT support. Epi Info™ is flexible, scalable, and free while enabling data collection, advanced statistical analyses, and geographic information system (GIS) mapping capability.”



EpiQuery: NYC Interactive Health Data

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Source: NYC Department of Health

Type: Online Database (web)

Level: Basic

Description: EpiQuery is a web-based, user-friendly system designed to guide users through basic data analyses on several datasets. EpiQuery Modules are based on individual health datasets with varying topics and indicators for different NYC populations.