History of Statistics

Since the beginnings of civilization, there have been simple forms of statistics, as there already were...
they used representationsgraphsand otherssymbolsin skins,rockssticks ofwoodand walls
from caves to count the number of people,animalsor things.
Around the year 3000 BC, the Babylonians used small clay tablets to record data.
about theproductionagricultural and on the goods sold or exchanged through barter. In the
31st century BC, long before building the pyramids, the Egyptians analyzed data from
thepopulationand the country's income.
Thebooksbiblical texts from Numbers and Chronicles include, in some parts, statistical work. The
first contains two censuses of the population ofIsraeland the second describes material well-being
from the various Jewish tribes. InChinathey existedrecordssimilar numerics prior to
Year 2000 BC. The classical Greeks conducted censuses whose information was used by around 594 BC.
to collecttaxes.TheRoman Empireit was the firstgovernmentthat collected a large amount
data on the population, area, and income of all the territories under itscontrol.During
theMiddle Ages only some thorough censuses were carried out inEurope.The caloring kings,
Pipino the Short and Charlemagne ordered thorough studies of the properties of
theChurchin the years 758 and 762 respectively. After theconquestnormanda
ofEnglandIn 1066, King William I of England commissioned the making of a census.
The information obtained from this census, carried out in 1086, is recorded in the Domesday Book.
Theregistrationthe registration of births and deaths began in England inprinciplesof the 16th century, and in
In 1662, the first notable statistical study of population appeared, titled Observations on the
London Bills of Mortality - Comments on the death records in London. A study
similar about the mortality rate in the city of Breslau,Germanymade in 1691, it was
used by the astronomerEnglishEdmund Halley as the basis for the first mortality table.
In the 19th century, with the generalization ofmethodscientist to study all the phenomena of
thesciencesnatural and social, the researchers accepted the need to reduce the
information tovaluesnumerical to avoid the ambiguity of verbal descriptions. In
In our days, statistics have become an effective method to describe with
accuracythe valuesof economic, political, social, psychological, biological or physical data, and
serves as a tool to relate and analyze that data.

Concept of Statistics

Statistics is a special technique suitable for the quantitative study of mass phenomena.
the collective, whose mediation requires a mass of observations of other simpler phenomena
individual or particular calls." (Gini, 1953).
Murray R. Spiegel, (1991) says: "Statistics studies themethodsscientists to collect,
organize, summarize, and analyze data, as well as to draw valid conclusions and make decisions
reasonable based on suchanalysis.
Statistics is a science that provides a set of methods used to collect,
summarize, classify, analyze and interpret the behavior of the data in relation to a
characteristicsubjectof study orresearch.Initially, it is responsible for obtaining
information, describe it and then use this information in order to predict something regarding the source of
information. (Moya Calderón, Rufino).
Statistics is theartto learn from the data. It is related to the collection of
data, yourdescriptionsubsequent and its analysis, which leads us to draw conclusions. (M. Ross,
Sheldon).
Whatever the point of view, the fundamental thing is the scientific importance that it has.
statistics, due to the vast field of application it has.

Classification of Statistics

We can define theStatistics Descriptivehow amethodfor describe

numericallysetsnumerous. (Vargas Sabadías, Antonio. 1995).
As it is a method of numerical description, descriptive statistics uses numbers
as a way to describe a set, which must be numerous, since the permanences
statistics are not given in rare cases. It is therefore not possible to draw concrete conclusions and
you need the statistical data. Descriptive Statistics deals with analysis and presentation
from the information, after its collection, statistical tables are prepared,graphicsand some
calculations.
Inferential statistics has asfunctiongeneralize the results of thesampleto estimate
the characteristics of thepopulation.However, the sample dataset can be described
or to be analyzed in the same way as a population. Therefore, the dataset or
observations of a sample can be used in a double sense: first, to describe the
own set of observations and, secondly, to infer or predict what happens in the population.
(Spagni De Barletta; 2005)
Consequently, the descriptive phase is common to any set of observations or data, whether
they refer to the entire population, a sample, or even a subpopulation. Statistics
Descriptive is the most classic, most recognized, and most fundamental part ofsciencestatistics.

Usefulness and importance of statistics in nursing

In today's world, Holmes (1980) points out that Statistics is necessary for a citizen
with general education, acquire the ability to read and interpret tables and graphs
statistics that appear in the news media, to orient themselves in a world linked by
telecommunications and interdependent and to interpret a wide range of information
about the most varied topics. Knowledge of statistics promotes personal development
it promotes critical reasoning, increases the ability to use quantitative data to
control our judgments and interpret those of others and transform them to solve problems of
decision y make predictions. (Ottaviani, 1998). In Nursing, the study of
Statistics provides the fundamental and necessary concepts with the appropriate mastery of
instrumental to approach the study and understanding of competition phenomena of the
Nursing. The practice of research and the transfer of knowledge produced to
professional practice constitutes the basic activity for the development of Nursing through
the social goal of responding to the problems and needs of the community is aspired to.
in the field of Health, research priorities require that the trained personnel and
works in the sector incorporate research as a permanent activity in their field of
action.
Relationships of other sciences with statistics
Statistics is a special technique suitable for the quantitative study of mass phenomena.
the collective, whose mediation requires a mass of observations of other simpler phenomena
individual or particular calls.
Murria R. Spiegel, (1991) says: "Statistics studies themethodsscientists to collect,
organize, summarize, and analyze data, as well as draw valid conclusions and make decisions
reasonable based on suchanalysis.
Statistics issciencewhich deals with the collection, classification, and presentation of facts
subject to a numerical appreciation based on the explanation, description, and comparison of the
phenomena". (Yale and Kendal, 1954).
Whatever the point of view, the fundamental thing is the scientific importance it has.
statistics due to the big field of application what it possesses.The
researchinPsychologySociologyyEducationas happens in other sciences, in good
the measure is based on the management of statistical resources as essential elements to achieve
acceptable conclusions by the rest of thecommunityscientific. Given the peculiarity of its object
of study, unapproachable in most cases unless through complex perspectives of
relationship betweenvariables,theattentionof researchers in the human and social sciences is
focus increasingly on what is called Multivariate Statistics. Complex designs
ofresearchand analysis, the most recent contributions of thecomputer sciencefor the application
oftechniquesadvanced data manipulation and the discussion of these aspects from
theoretical and applied perspectives, concern and focus a multitude of professionals whose
Everyday activity is the study of how research is conducted, making it their specialty.
At the same time, other specialties within these sciences useknowledgealready prepared
and retransmitted, more worried about the results and possibilities than about the conditions of
application and the basis for use, in such a way that the use of techniques has been encouraged
statistics, without considering their adequacy to the conditions under which they are applied.
At the same time, thesocial
scienceshave been overwhelmed in recent years by rapid advances
in computing and statistical applications (Manheim, 1982; Rossi and others, 1983), and very
especially in psychology (Judd et al., 1995), which favors an absorption of
littlequalityby specialists in non-methodological areas. On the other hand,
theadoptionofproceduresIT professionals to carry out methodological tasks does not seem to be a
immediate solution, considering the anxiety generated by computers, a very common phenomenon
generalized (Fariña and Arce, 1993).
Thefusionfrom this growing complication of thetoolsof analysis, along with the discrepancy
among theobjectivesof training and the need to use statistical resources, achieves
finally, that the specialist in applied areas tends to neglect very basic, prior aspects
to the application of these complex statistical resources. On the other hand, on many occasions, the
the application of statistical tools is dragged byhypothesisof comfort, in the sense
to apply to allow the execution of a test or the adjustment of amodelnot because they are
thestrategiesmore suitable, but because they are the most comfortable
Statistical physics or statistical mechanics is the part of thephysicswhat it seeks to determine
thebehaviorthermodynamic aggregate ofsystemsmacroscopic a starting from
microscopic considerations using statistical tools along with
alawsmechanics.
Statistical physics can describe numerous fields with anaturestochastic (reactions
nuclear, biological, chemical, neurological systems, etc.
Industrial statistics is the branch of statistics that seeks to implement
theprocessesprobabilistic and statistical analysis and interpretation of data or characteristics of
a set of elements to the industrial environment, in order to assist in thedecision makingand in
thecontrolof industrial and organizational processes.
History is the science that studies the past of humanity and
howmethodthe own of the social sciences. It is also called history to the historical period
that unfolds from the appearance of thewritingup to the present.
It is considered "the science of sciences" because it encompasses the study of many other sciences.
prior to the relationship with her. Beyond the specific meanings of historical science, history inthe
languageIt is usual to narrate any event, including imaginary events and lies.
In medicine, theconceptof medical history for the registration of health data
significant to a patient, tracing back to their birth or even to
oninheritancegenetics.
In history, statistics play a role.functionprimordial forto be ablelocate in time and in the
space each of the events since the creation of theuniverse.
Biostatistics, in a general way, is the application of statistics to thebiologyDue to the
The issues to be investigated in biology are of a very varied nature, for example, medicine,
agricultural and forestry sciences, biostatistics has expanded its domains to include
any quantitative model, not just statistical, that can be used to respond to these
needs.
Biostatistics can be considered as a highly specialized branch of the
medical informatics that can, in turn, be complemented by bioinformatics.
Some fields of research use statistics so extensively that they have their own terminology.
specialized. These disciplines include:
Actuarial sciences
Statistical physics
Industrial statistics
Spatial Statistics
Mathematics Statistics
Statistics in Medicine
Statistics in Nutrition
Statistics in Agronomy
Statistics in Planning
Statistics in Research
Statistics in Law
Statistics in Artwork Restoration
Statistics in Literature
Statistics in Astronomy
 Statistics in theAnthropologyAnthropometry
Statistics in History
Military Statistics
Geostatistics
Biostatistics
Business Statistics
Computational Statistics
Statistics in Health Sciences
Operations Research
Consulting Statistics
Statistics ofeducationtheteachingand the training
Statistics in themarketingmarketing
Bibliometrics
Environmental Statistics
Statistics in Epidemiology
Data mining (applies statistics and pattern recognition to theknowledgeof
data
Economic statistics (Econometrics)
Statistics in Engineering
Geography andInformation systemsgeographical, more specifically in Spatial Analysis
Demography
Statistics in psychology (Psychometrics)
Quality and productivity
Social statistics (for all social sciences)
Statistical culture
Sampling Surveys
Process analysis and chemometrics (for data analysis inchemistryanalytics
andengineeringchemistry

Sports Statistics

Definition of population from the statistical point of view

Population, in statistics, also calleduniversethe collective is defined as any set

of people, objects, ideas, or events that are subjected to theobservationstatistic of a
or several characteristics that their elements share and that allow them to be differentiated.
Fernández, Santiago
The meaning given to the word population in Statistics is broader than that used inthe
languagehabitual, referred exclusively to a group of people. They are populations based on
example, the different cars found in a dealership or the
differentreligionsfrom a country. Can the different factories of a country be considered as population?
an industrial sector? And to the students of aclass?And at thereligionsof the world? And to each one
of the days of a month?
The answer is affirmative in all cases. In statistics, the word 'population' not only refers to
it refers to people, such as students, but also objects, ideas, or events,
like factories, religious beliefs, or days.

Types of population and how they are denoted

The population can be:

Finite population: the number of elements that make it up is finite, for example the number of
students from a center ofteaching.
Infinite population: the number of elements that make it up is infinite, or so large that it could be
to consider themselves infinite. For example: if a study were to be conducted on theproductsWhat's up
in themarket. Hthere are so many and of so many qualities that this population could be considered infinite.
Base population: it is the group of people designated by the following characteristics:
personal, geographical or temporal, that are eligible to participate in the study.
Sampled population: it is the base population with feasibility or possibility criteria.
to be heldsampling.Example:Effectivenessof a drug for sick patients ofpagein the USA.
Target population: it is the group of people to whom the study is directed, the classification.
characteristic of them, which makes itmodelfor studyprojectestablished.
Example: Population of undergraduate students in Accounting between the ages of 18 and 23.

What is a qualitative measure?

It isvariablesthat express different qualities, characteristics, or modality. Each modality

what is presented is called an attribute or category and the measurement consists of a classification of
such attributes. They cannot be measured numerically (for example:nationalitycolorof theskin
gender). Qualitative variables can be ordinal and nominal.

What is a quantitative measure?

They are the variables that are expressed through numerical quantities, that is, they havevaluenumeric
agepriceof aproduct,incomeannual).
What is a discrete variable?

It is the variable that exhibits separations or interruptions in the scale of values that can
take. These separations or interruptions indicate the absence of values between the different
specific values that the variable can take. They can only take integer values (1, 2, 8, -4,
etc.). For example: number of siblings (it can be 1, 2, 3...., etc., but, for example, it can never be
be 3.45).

What is a continuous variable?

It is the variable that can take any value within a specified range of values.
For example, weight or height, which is only limited by the precision of the measuring device,
intheorythey allow that there is always a value between any two. They can take any
real value within an interval. For example, thespeedthe speed of a vehicle can be 90.4 km/h,
94.57 km/h...etc.

Type of scale

Nominal scale: It uses numbers to identify that a data point belongs to a group or to a
category. It is a scale that does not have a particular order or dimension, they are
observations that can be classified or counted. In data analysis it is easier
assign numerical 'labels' to certain attributes instead of using complex data. Therefore
we can use a "1" to designate women and a "2" to designate men, without
that none of the numbers represent more or less, solely with the aim of distinguishing and
organize data. On this scale eachpersonthe object must belong to one and only one
of the categories they have and the set of these categories must be exhaustive; that is,
It must cover all possible cases.
Ordinal scale: In this scale, the numbers represent a ranking (greater than or less than)
that), without representing a unit of measurement, implicitly indicating that a larger number
amount has a higher degree of attribute measured in comparison to a smaller number. It
establish a gradation or natural order for the categories, each of the data can
to locate oneself within one of the available categories.
Interval scale: In this scale, in addition to 'greater than' and 'less than,' there is also
establishes a unit of measure that allows us to specify how much greater or lesser one is.
the unit of measurement is arbitrary, zero is conventional and negative quantities can exist;
the measurement ofthe temperatureand the intelligence quotient are examples of this type of scale.
On this scale, comparisons can be made through differences or sums, without
embargo comparisons through multiplications, divisions or percentages are not allowed
well, they lack meaning.
Ratio scale: Similar to the interval scale, but it has an absolute zero and therefore the
multiples of the values of the scale will be significant; the level of votes in an election would be
a good example of a ratio scale.