importance of Descriptive statistics

importance of Descriptive statistics

1. Tools for troubleshooting and correct decision-making decisions in different areas of statistics.

   • In psychology
     • It allows extracting and summarizing useful information from the observations that are made, the psychologist You must base your decisions on limited data and these are easier to take with the help of statistics, gives you greater clarity and precision psychological thought and research.
     • Statistical planning of the Investigation: Locate the information sources, choose the material. raise a study problem.
       • In the health
         • Statistics in health is a discipline scientist responsible for the collection, analysis, processing, and presentation of all information generated in establishments of medical and health care, with the aim of contribute to proper decision-making, enabling problem solving health-disease of the population.
         • Statistics are present in the analysis of the situation of health, the identification of risk factors, the epidemiological surveillance, policy development and intervention evaluation. In this way, it contributes to the generation of reliable population health data for decision making.
         • Grants a discernment of health problems for that are efficiently applied the resources available for solve them.
           • In the economy
             • provides methods that allow the analysis of economic facts, highlighting their most important characteristics and fixing, furthermore, including the limitations, conditions and scope of the conclusions that said analysis can be extracted.
             • It is of the utmost importance so that behavior is known from the economy to different levels either in a company, municipality, province, nation, as well as internationally.
               • In companies
                 • Allows descriptions of populations or samples of interest for companies, through Descriptive Statistics, transforming the data into information presented in tables of frequency distribution, graphs and measures of trend central, variability and shape of empirical distributions of frequencies.
                 • Allows estimation of population parameters from samples, corroborate hypotheses about the value of a parameter (parametric approach); Classify subject elements, individuals, units, events, based on their own characteristics of them, Provides techniques for measuring performance employment in the company, allows detecting patterns of behavior on the data.
                 • With statistics you can analyze survey data by sampling or census and Allows data analysis of feasible projects, data administrative and data any database (qualitative and quantitative).
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             • Statistics in the economy allows to support the decision decisions for the application of the economic policy that countries propose to lead society, as well as to draw up the development strategy in accordance with the programs that are considered according to the prevailing conditions in each nation.
     • Design the experiment. The model is validated compared to what happens in the reality. Statistical methods are used known as hypothesis tests or tests of significance.
   • Two measures of descriptive statistics
     • Measures of central tendency: The most commonly used measures are the mean, median, and mode.
     • Variability measures: The most used measures are variance and kurtosis.

2. The importance of descriptive statistics is to highlight characteristic aspects of the group (averages, data variability, etc.) that serve to make comparisons, without trying to draw more general conclusions. This description is usually done through the preparation of charts, graphs, calculation of averages, proportions, and variances of one or more related variables. Martinez, B. (2018).

   • inside the statistics descriptive, we can describe the data in a qualitative way or quantitative.
     • Variable quantitative
       • Variables that take numerical values. Example: number of houses, age etc.
         • Tools used for analysis :
           • Radar Chart (Spider Diagram), Grid of Selection, Graph of Behavior, Sheet of Review, Pareto Chart, Cost/Benefit Analysis, Distribution Diagram, Histogram.
     • qualitative variable
       • are the variables that can take qualities as values or categories. Example: nationality, skin color, sex etc.
         • tools used to the analysis :
           • Flowchart, Affinity Diagram, Checklist for Data Collection, Checklist for Definition of Problems, Analysis of the Field of Forces, Interrelationship Diagram, Diagram of Cause and Effect.

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