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Espai Nightingale

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Aquest glossari és una mostra dels camps més representatius en què la Florence Nightingale va treballar. 


Causes of mortality

The most frequently occuring causes of mortality (usually 10) under which the greatest number of deaths have been reported during a given year. Causes of mortality are all those diseases which either resulted in or contributed to death, and the circumstances of the accident or violence that produced any such injuries. The crude mortality rate is usually expressed as the number of deaths from a specific cause per 100 000 population for a given year.

Citació: "Causes of mortality" A: The Global Health Observatory. World Health Organization. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://www.who.int/data/gho/indicator-metadata-registry/imr-details/3704>

Crimean war

The Crimean War was a military conflict fought from October 1853 to February 1856 in which Russia lost to an alliance made up of the Ottoman Empire, the United Kingdom, Sardinia and France. The immediate cause of the war involved the rights of Christian minorities in the Holy Land, which was a part of the Ottoman Empire. The French promoted the rights of Roman Catholics, while Russia promoted those of the Eastern Orthodox Church. The longer-term causes involved the decline of the Ottoman Empire and the unwillingness of Britain and France to allow Russia to gain territory and power at the Ottoman Empire's expense. It has widely been noted that the causes, in one case involving an argument over the keys to the Church of the Nativity, revealed a "great confusion of purpose", yet they led to a war noted for its "notoriously incompetent international butchery"

Citació: "Crimean war" A: Wikipedia. Wikimedia Foundation, 2011. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Crimean_War>

Data visualization or Statistical visualization

Data visualization is the graphic representation of data. It involves producing images that communicate relationships among the represented data to viewers of the images. This communication is achieved through the use of a systematic mapping between graphic marks and data values in the creation of the visualization. This mapping establishes how data values will be represented visually, determining how and to what extent a property of a graphic mark, such as size or color, will change to reflect changes in the value of a datum.

To communicate information clearly and efficiently, data visualization uses statistical graphics, plots, information graphics and other tools. Numerical data may be encoded using dots, lines, or bars, to visually communicate a quantitative message. Effective visualization helps users analyze and reason about data and evidence. It makes complex data more accessible, understandable and usable. Users may have particular analytical tasks, such as making comparisons or understanding causality, and the design principle of the graphic (i.e., showing comparisons or showing causality) follows the task. Tables are generally used where users will look up a specific measurement, while charts of various types are used to show patterns or relationships in the data for one or more variables.

Data visualization is both an art and a science. It is viewed as a branch of descriptive statistics by some, but also as a grounded theory development tool by others. Increased amounts of data created by Internet activity and an expanding number of sensors in the environment are referred to as "big data" or Internet of things. Processing, analyzing and communicating this data present ethical and analytical challenges for data visualization. The field of data science and practitioners called data scientists help address this challenge.

Citació: "Data visualization" A: Wikipedia. Wikimedia Foundation, 2011. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Data_visualization>

The Lady with a Lamp or Florence Nightingale

Florence Nightingale (12 May 1820 – 13 August 1910) was an English social reformer, statistician and the founder of modern nursing. Nightingale came to prominence while serving as a manager and trainer of nurses during the Crimean War, in which she organised care for wounded soldiers. She gave nursing a favourable reputation and became an icon of Victorian culture, especially in the persona of "The Lady with the Lamp" making rounds of wounded soldiers at night.

Citació: "Florence Nightingale" A: Wikipedia. Wikimedia Foundation, 2011. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Florence_Nightingale>

Medical statistics

Medical statistics deals with applications of statistics to medicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research. Medical statistics has been a recognized branch of statistics in the United Kingdom for more than 40 years but the term has not come into general use in North America, where the wider term 'biostatistics' is more commonly used. However, "biostatistics" more commonly connotes all applications of statistics to biology. Medical statistics is a subdiscipline of statistics. "It is the science of summarizing, collecting, presenting and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses. It has a central role in medical investigations. It not only provides a way of organizing information on a wider and more formal basis than relying on the exchange of anecdotes and personal experience, but also takes into account the intrinsic variation inherent in most biological processes." 

Citació: "Medical satatistics" A: Wikipedia. Wikimedia Foundation, 2011. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Medical_statistics>

Mortality rate

Mortality rate, or death rate,[3]:189,69 is a measure of the number of deaths (in general, or due to a specific cause) in a particular population, scaled to the size of that population, per unit of time. Mortality rate is typically expressed in units of deaths per 1,000 individuals per year; thus, a mortality rate of 9.5 (out of 1,000) in a population of 1,000 would mean 9.5 deaths per year in that entire population, or 0.95% out of the total. It is distinct from "morbidity", which is either the prevalence or incidence of a disease, and also from the incidence rate (the number of newly appearing cases of the disease per unit of time).[3]:189[verification needed]

An important specific mortality rate measure is the crude death rate, which looks at mortality from all causes in a given time interval for a given population. As of 2020, for instance, the CIA estimates that the crude death rate globally will be 7.7 deaths per 1,000 persons in a population per year.[4] In a generic form,[3]:189 mortality rates can be seen as calculated using {\displaystyle (d/p)\cdot 10^{n}}{\displaystyle (d/p)\cdot 10^{n}}, where d represents the deaths from whatever cause of interest is specified that occur within a given time period, p represents the size of the population in which the deaths occur (however this population is defined or limited), and {\displaystyle 10^{n}}10^{n}is the conversion factor from the resulting fraction to another unit (e.g., multiplying by {\displaystyle 10^{3}}10^{3}to get mortality rate per 1,000 individuals).[3]:189

Citació: "Mortality rate" A: Wikipedia. Wikimedia Foundation, 2011. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Mortality_rate>


Nosology (from Ancient Greek νόσος (nosos) 'disease', and -λογία (-logia) 'study of-') is the branch of medical science that deals with the classification of diseases. Fully classifying a medical condition requires knowing its cause (and that there is only one cause), the effects it has on the body, the symptoms that are produced, and other factors. For example, influenza is classified as an infectious disease because it is caused by a virus, and it is classified as a respiratory infection because the virus infects and damages certain tissues in the respiratory tract. The more that is known about the disease, the more ways the disease can be classified nosologically.

Nosography is a description whose primary purpose is enabling a diagnostic label to be put on the situation. As such, a nosographical entity need not have a single cause. For example, inability to speak due to advanced dementia and an inability to speak due to a stroke could be nosologically different but nosographically the same.

Citació: "Nosology" A: Wikipedia. Wikimedia Foundation, 2011. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Nosology>

Polar area diagram or Nightingale rose diagram or Nightingale's “Coxcombs”

The polar area diagram is similar to a usual pie chart, except sectors have equal angles and differ rather in how far each sector extends from the center of the circle. The polar area diagram is used to plot cyclic phenomena (e.g., counts of deaths by month). For example, if the counts of deaths in each month for a year are to be plotted then there will be 12 sectors (one per month) all with the same angle of 30 degrees each. The radius of each sector would be proportional to the square root of the death count for the month, so the area of a sector represents the number of deaths in a month. If the death count in each month is subdivided by cause of death, it is possible to make multiple comparisons on one diagram, as is seen in the polar area diagram famously developed by Florence Nightingale.

The first known use of polar area diagrams was by André-Michel Guerry, which he called courbes circulaires (circular curves), in an 1829 paper showing seasonal and daily variation in wind direction over the year and births and deaths by hour of the day. Léon Lalanne later used a polar diagram to show the frequency of wind directions around compass points in 1843. The wind rose is still used by meteorologists. Nightingale published her rose diagram in 1858. Although the name "coxcomb" has come to be associated with this type of diagram, Nightingale originally used the term to refer to the publication in which this diagram first appeared—an attention-getting book of charts and tables—rather than to this specific type of diagram.

Citació: "Polar area diagram" A: Wikipedia. Wikimedia Foundation, 2011. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Pie_chart#Polar_area_diagram>

Statistical graphics

Statistical graphics, also known as graphical techniques, are graphics in the field of statistics used to visualize quantitative data.

Whereas statistics and data analysis procedures generally yield their output in numeric or tabular form, graphical techniques allow such results to be displayed in some sort of pictorial form. They include plots such as scatter plots, histograms, probability plots, spaghetti plots, residual plots, box plots, block plots and biplots.

Exploratory data analysis (EDA) relies heavily on such techniques. They can also provide insight into a data set to help with testing assumptions, model selection and regression model validation, estimator selection, relationship identification, factor effect determination, and outlier detection. In addition, the choice of appropriate statistical graphics can provide a convincing means of communicating the underlying message that is present in the data to others.

Citació: "Statistical graphics" A: Wikipedia. Wikimedia Foundation, 2011. [en línia]. [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Statistical_graphics>


Statistics is the discipline that concerns the collection, organization, analysis, interpretation and presentation of data. In applying statistics to a scientific, industrial, or social problem, it is conventional to begin with a statistical population or a statistical model to be studied. Populations can be diverse groups of people or objects such as "all people living in a country" or "every atom composing a crystal". Statistics deals with every aspect of data, including the planning of data collection in terms of the design of surveys and experiments.

Citació: "Statistics " A: Wikipedia. Wikimedia Foundation, 2011. [en línia].  [Consulta: 6 d'octubre 2020]. Disponible a: <https://en.wikipedia.org/wiki/Statistics>

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