Rtabnetsp: an R package for retrieving São Paulo State health status indicators, Brazil

João Henrique de Araújo Morais1, Thais Cláudia Roma de Oliveira Konstantyner2, Álvaro Luiz Fazenda3

  • 1Fundação Oswaldo Cruz, Escola Nacional de Saúde Pública Sergio Arouca, Rio de Janeiro, RJ, Brasil.

Related Concept Videos

Statistical Methods for Analyzing Epidemiological Data01:25

Statistical Methods for Analyzing Epidemiological Data

Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
680
Statistical Software for Data Analysis and Clinical Trials01:12

Statistical Software for Data Analysis and Clinical Trials

Statistical software is pivotal in data analysis and clinical trials by providing tools to analyze data, draw conclusions, and make predictions. These software packages range from simple data management applications to complex analytical platforms, supporting various statistical tests, models, and simulation techniques. Their significance lies in their ability to handle vast amounts of data with precision and efficiency, enabling researchers to validate hypotheses, identify trends, and make...
1.1K
Statistical Package for the Social Sciences (SPSS)01:22

Statistical Package for the Social Sciences (SPSS)

The Statistical Package for the Social Sciences, or SPSS, is a data management and analysis software suite. Developed by SPSS Inc. in 1968 and acquired by IBM in 2009, this tool was initially designed for social science data analysis, evolving to serve a wider range of disciplines. It was later renamed to Statistical Product and Service Solutions.
SPSS streamlines the process from data preparation to analysis and reporting. It is characterized by its user-friendly interface, which conceals...
748
Overview of Biostatistics in Health Sciences01:19

Overview of Biostatistics in Health Sciences

Biostatistics involves the application of statistical techniques to scientific research in health-related fields, including biology and public health. These techniques are essential for designing studies, collecting data, and analyzing it to draw meaningful conclusions. Given the complexity of biological processes, particularly in studies involving human subjects, biostatistical methods are crucial for effectively organizing and interpreting data that might otherwise obscure underlying patterns...
3.7K
Biostatistics: Overview01:20

Biostatistics: Overview

Biostatistics plays a crucial role in understanding and analyzing data in healthcare and biology. Biostatisticians conduct experiments, gather evidence, and draw meaningful conclusions using statistical methods and techniques. Different variables form the foundation of biostatistical analysis, allowing researchers to understand and interpret data effectively. These variables are classified into different types, each serving a specific purpose in statistical analysis.
Discrete variables are...
453
Statistical Analysis System (SAS)01:14

Statistical Analysis System (SAS)

SAS, short for Statistical Analysis System, is a powerful data analysis, management, and visualization tool. Developed by the SAS Institute in the early 1970s, SAS has evolved into a comprehensive software suite used across various industries for statistical analysis, business intelligence, and predictive modeling.
Applications: SAS finds applications in numerous fields, including healthcare for clinical trial analysis, finance for risk assessment, marketing for customer data analysis, and...
514