Statistics is a set of methods used to collect, summarize, classify, analyze and interpret the behavior of data with respect to a characteristic, subject of study or research. Statistics is considered as a collection of numerical facts expressed in a summative way, and that have been compiled from other numerical data. It is considered as the visual and analytical calculation of the different types of samples found in a population, it is a special technique suitable for quantitative study and it is considered as one of the very useful economic, social and natural sciences.
What does statistics mean?
The word statistics comes from the Latin statisticumcollegium and means ("council of state") and from its Italian derivative statista ("statesman" or "politician"). The term statistics is widely heard in various parts of the world. However, since the beginning of civilization there have been simple forms of statistics, since graphical representations and other symbols were already used on skins, rocks, wooden sticks and cave walls to count the number of people, animals or certain things. We find it in our daily lives, usually its meaning is: numerical information.
Why is statistics studied?
Statistics allow us to provide the basic elements to support an investigation, how to plan the obtaining of data so that reliable conclusions can be drawn from them, how to analyze these data, what type of conclusions can be obtained with the available data, what is the confidence that the data deserve us. Statistics, as can be seen, allow us to carry out descriptive and explanatory studies in practically all areas, through it we can know the numerical and descriptive situation of a company, community, business, among others.
What is the usefulness of statistics?
Statistics provide us with answers to many of the needs that today's society poses to us. Its fundamental task is the collection of data, with the aim of representing reality and transforming it, predicting its future or simply knowing it. It allows us to obtain (The Quality Control) allows us to measure the characteristics of the quality of a product, compare them with certain requirements and make corrective decisions if there are differences between the actual and expected performance. In Agriculture and Fishing we can estimate the yields obtained in a harvest, or estimate the production of fish.
Statistical types
- Descriptive: It is the technique that is going to be in charge of the collection, presentation, treatment and analysis of the data, in order to summarize, describe the characteristics of a set of data and generally take the form of tables and graphs. Inferential: Technique by which conclusions or generalizations are drawn about parameters of a population. It draws useful conclusions about the totality of all possible observations based on the collected information and they are considered as hypothetical calculations.
Population
A population is specified as a finite or infinite set of people or objects that have common characteristics. According to Levin & Rubin (1996). »A population is a set of all the elements that we are studying, about which we try to draw conclusions». The size of a population is an extremely important factor in the statistical research process and in our social case, and this size is given by the number of elements that make up the population, depending on the number of elements the population can be finite or infinite. When the number of elements that make up the population is very large, it can be considered an infinite population.
Parameters
A statistical parameter is a number that is obtained from the data of a statistical distribution. It is a number that summarizes the large amount of data that can be derived from the study of a variable. The calculation of this number is well defined, usually by means of an arithmetic formula obtained from population data. Studying a large amount of individual data from a population can be cumbersome and inoperative, so it is necessary to make a summary that allows a global idea of the population to be obtained. Statistical parameters are an inevitable consequence of the essential purpose of statistics: to create a model of reality.
Shows
A sample is a subset of cases or individuals of a population, the samples are obtained with the intention of observing properties of the entire population, therefore they must be representative of it. To fulfill this characteristic, the sample must go through a technique called sampling. In such cases, information similar to that of a comprehensive study can be obtained more quickly and at less cost. On the other hand, sometimes, the sampling can be more exact than the study of the entire population because the handling of a smaller number of data also causes fewer errors in its manipulation.
What is statistical?
In statistics, a statistic is a quantitative measure, derived from a set of data from a sample, with the objective of estimating or inferring characteristics of a population or statistical model. A statistic, as a function of random variables, is also a random variable and as such acquires different values from one sample to another. The value of the statistic obtained using the observed values in this function can be used in a statistical test or as an estimate of a population parameter, such as a mean or standard deviation.
What are data or variables?
The variables, also usually called quantitative characters, are those that can be expressed by numbers. They are measurable characters. Like for example, height, weight, salary, age, etc. All the elements of the population have the same types of characters, but since these are generally not represented with the same intensity, it is obvious that the variables take different values. Therefore these different numbers or measurements that the characters take are the "values of the variable." All of them together constitute a variable.
Why do we need to collect data?
In statistics, data collection provides us with the essential introduction for a research study, it helps us measure performance in a service or production process, it is essential for formulating alternatives for decision-making and seeking to satisfy our curiosity. Data collection refers to the use of a great diversity of techniques and tools that can be used by the analyst to develop information systems, which can be interviews, surveys, questionnaires, observations, flow charts. and the data dictionary.
Type of data
Statistical data can be of two types:
- Qualitative: they are those in which the possible results are not numerical values. For example: hair color, type of preferred clothing, summer resort, etc. Quantitative: those whose result is a number. In turn, there are two types: Quantitative Discrete: when isolated values are taken. For example: number of friends in your gang, number of times you go to the movies per month, number of cars your family has. Quantitative Continuous: when, between any two values, there can be intermediate values. That is, all the values of a certain interval are taken. For example: weight of people, level above sea where your city is located, measurement of the thoracic perimeter.
Surveys and their types
The survey can be considered as a technique or a strategy understood as a set of processes necessary to obtain information from a population through interviews with a representative sample. The information is collected in a structured way by formulating the same questions and in the same order to each of the respondents. Although it can be used independently, its results improve when they are previously contextualized in a bibliographic theoretical framework and when they are accompanied by qualitative techniques. Among its types are:
According to your goals
- Descriptive Surveys: Reflect or document the present attitudes or conditions. This means trying to describe what situation a certain population is in at the time the survey is being conducted. Analytical Surveys: Instead they seek, in addition to describing, to explain the whys of a certain situation. In this type of survey, the hypotheses that support them are usually contrasted by examining at least two variables, of which interrelationships are observed and then explanatory inferences are formulated.
According to the questions
- Open Response: In these surveys, the respondent is asked to answer the question asked. This gives the interviewee greater freedom and at the same time makes it possible to acquire deeper answers as well as ask about the why and how of the answers made. On the other hand, it allows you to acquire responses that had not been taken into account when making the forms and thus can create new relationships with other variables and responses. Closed Response: In these, respondents must choose to answer one of the options that are presented in a list formulated by the researchers. This way of surveying results in answers that are easier to quantify and of a consistent nature.The problem that these surveys can present is that there is no option in the list that matches the answer that you want to give, so the ideal is always to add the option "other".
El cuestionario y tipos de preguntas:
Un cuestionario es un instrumento de investigación que consiste en una serie de preguntas y otras indicaciones con el propósito de obtener información de los consultados. En los cuestionarios pueden aparecer diferentes tipos de preguntas según las características del tema a investigar. En general, pueden aparecer en los cuestionarios los siguientes tipos de preguntas:
- Abiertas: Permiten responder en cualquier sentido de acuerdo con sus ideas. No circunscriben las respuestas a alternativas predeterminadas. Estas preguntas, además del inconveniente de que exigen más tiempo al entrevistador y más esfuerzo para el entrevistado son de difícil codificación. Cerradas: Permiten responder con una (si/no) o varias de las alternativas existentes (si/no/no sabe o no contesta). A pesar del inconveniente de su compleja redacción y limitada riqueza expositiva son preguntas muy fáciles de responder y codificar y además de favorecer la comparabilidad con otras respuestas reduce la ambigüedad de éstas. Semicerradas ó Semiabiertas: Contienen una serie de posibles respuestas previamente establecidas y una respuesta abierta tipo “otros “para incorporar respuestas de opinión.
Relación entre técnicas e instrumentos
Un instrumento de recolección de datos es en principio cualquier recurso de que pueda valerse el investigador para acercarse a lo que se quiere investigar y extraer de ellos información. De este modo el instrumento sintetiza en si toda la labor previa de la investigación, por técnica entendemos que es un conjunto de mecanismos, medios y sistemas de dirigir, recolectar, conservar, reelaborar y transmitir los datos. Las técnicas están referidas a la manera como se van a obtener los datos y los instrumentos son los medios materiales, a través de los cuales se hace posible la obtención y archivo de la información requerida para la investigación. Se relacionan entre sí porque por medios de ellos la información que se necesita para una investigación es más fácil de encontrar.
A continuación una completa video lección en la cual se presentan algunas de las definiciones básicas de la ciencia estadística, incluyendo, por supuesto, la respuesta a la pregunta ¿qué es estadística? (TareasPlus.com)
Bibliografía
- http://www.monografias.com/trabajos60/estadistica/estadistica.shtmlwww.significados.com/estadisticawww.dorasierra.galeon.com/aficiones280542.htmlDra. Luz M. Rivera CREMC 2000 – 2001 Derechos Reservados. Última Edición: Marzo 9, 2001.https://es.wikipedia.org/wiki/Estad%C3%ADsticahttp://www.vitutor.com/estadistica/descriptiva/a_7.htmlhttp://es.slideshare.net/ChrisZtar/recoleccin-de-datos-estadsticoshttp://www.monografias.com/trabajos12/recoldat/recoldat.shtml#ixzz3RSmgBGXDwww2.uah.es/vicente_marban/ASIGNATURAS/…/tema%205.pdf
