As health care evolves in our nation, the role of research and statistics will evolve right along with it. There will be more research into medical care, health care costs, medications, and types of treatments. The most common types of statistics reported will be the fertility rates, which includes vital statistics (birth, death, marriage, divorce rates), morbidity (the incidence of disease in a population), and mortality (the number of people who die in a certain disease compared with the total number of people). As stated above, health care costs along with demographic distribution based on geographic, ethnic, and gender variables, and data on the socioeconomic status and education of health care professionals are also common statistical data reported. As the role of research and statistics are looked into more deeply, we will discuss the different types of variables used, examine independent and dependent variables more closely, and evaluate the characteristics of primary and secondary data as used in research and statistics.
Research will begin with collecting data and obtaining the variables. Data and variables go hand in hand as the data is the value of the variable. The most common types of variables are quantitative or qualitative data/variables. The quantitative variables consist of numerical variables, and the numerical variables can be described as continuous or discrete. Examples of this can be numbers expressed in weights, distance, age, dollars, etc. This can also be broken down into interval and ratio levels of measurement. Qualitative variables are more categorical. They are arranged by examples of colors, sex, yes/no answer choices, letter grades, etc. Qualitative variables can be considered as nominal and ordinal levels of measurement. Qualitative and quantitative variables are very common types of variables. They represent all types of numerical data and categorical data that are
References: Triola, MD, Marc M., & Triola, Mario F. (2006). Chapter 1: Introduction 1-2 Types of Data & 1-3 Design of Experiments, Chapter 2 : Describing, Exploring, and Comparing Data, 2-3 Visualizing Data. In D. Lynch, K. Nopper, S. Oliver, & R. Hampton, Biostatistics for the Biological and Health Sciences (pp. 4-13 & 33-40) Boston, MA: Pearson Education, Inc. Kaps, Miroslav, & Lamberson, William R. (2009). Biostatistics for Animal Sciences an Introductory Science, 2nd ed. Retrieved from http://bookshop.cabi.org/Uploads/Books/PDF/9781845935405/9781845935405.pdf The International Development Research Centre, Science for Humanity: Designing and Conducting Health System Research Projects: vol. 1. Retrieved from http://www.idrc.ca/en/ev-56602-201-1-DO_TOPIC.html