Definition Statistics By General and Definition Complete

Already know about Statistics? What are statistics? Still confused? You are right here, because Citra will tell you more in RODA Statistics.
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Definition Statistics By General and Definition Complete

Already in the know about Statistics? Statistics that what? Still confused? You guys are right here because Citra will know more about RODA Statistics. Let's start reading and understanding about Definition of Statistics.

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What are that Statistics?

Statistics is a branch of knowledge mathematics application consisting of theory and method about how methods collect, measure, classify, calculate, explain, synthesize, analyze, and interpret the data obtained systematically. With so, inside consists of a bunch of procedures about how way:

  • Collect data
  • Summarizing data
  • Processing data
  • Presenting data
  • Interesting conclusion and interpretation of data based on the data set and results of the analysis

The article will outline the understanding and differences between statistics vs. parameter, method statistics, statistics descriptive vs. stats inferential, statistical math vs. stats applied, statistics parametric vs. non-parametric, and statistics univariate and multivariate as well as role statistics in research.

Statistics vs. Parameters:

  • Statistics (not statistics):
    • A collection of data, numbers and non-numbers arranged in tables and /or diagrams depicting or describing something problem
      • Statistics Population, birth, education, production, agriculture, etc.
    • Size as representative of a data set
      • Average, median, mode, deviation standard, variance, percent, etc.
  • Parameters are almost identical to statistics; the difference lies in the data source used. Statistics use source data originating from a sample, while the parameter uses source data arising from the population.
  • Statistics are used for estimating the score of population parameters.

Method Statistics

Method Statistics is the procedure used to collect, present, analyze, and interpret data.

Scope Statistics

  • Based on orientation, the discussion:

    • Statistics math

      : statistics is more theoretically oriented to understanding models and techniques of statistics by mathematical theory.
    • Statistics applied

      : more statistics oriented to understanding intuitive concepts and techniques and their use in various fields.
  • Based on stages and goals, the analysis:

    • Statistics descriptive:

      • Descriptive related with application method statistics about the collection, processing, and presentation of something data cluster to give helpful information.
      • Statistics use data on a group to explain or make an interesting conclusion about a group.
      • Explain/describe various data characteristics through:
        • Measures (Central Tendency): mode, mean, median, etc.
        • Size Variability / Dispersion: variance, deviation standard, range, etc.
        • Size Form: skewness, kurtosis, box plot.
        • Presentation tables and graphs, for example.
          • Distribution Frequency
          • Histogram, Pie chart, Boxplot, etc.
    • Statistics Inferential:

      • Statistics inference (inference statistics) is branch knowledge-related statistics with application statistics for assets and/ or testing characteristics hypothesized population based on sample data.
      • Statistics using data from something sample for an exciting conclusion about a population where is the example from the taken
      • Make various inferences (withdrawal) conclusions) to a collection of data from a sample. Inference action: Forecasting, forecasting, making decisions, and so on.

Destination from statistics basically is to do a description of the sample data, then To make inference to population data based on information (results statistics descriptive) contained in a sample. In practice, the second part of statistics is used together, generally starting with descriptive statistics and then following with various analysis statistics for inference.

Based on the assumption distribution used:

  • Statistics parametric:

    • Techniques measurement statistics based on certain assumptions, for example, the data taken from a normally distributed population.
    • Statistical technique this used for scalable data intervals and ratios.
  • Non-Parametric statistics:

    • Techniques statistics that use an unreasonable assumption (or even no same one) are sometimes also known as a statistical model that is free to distribute specific.
    • Non- parametric statistics this used for analyzing scalable data, nominal and ordinal.
  • Generally

    , every technique data testing with technique statistics parametric has a technique equivalent to non-parametric statistics. Equivalent courses in non-parametric statistics are normally used if interval/ ratio data no Fulfill certain assumptions; for example, the data is not normally distributed. For instance, if the data to be analyzed using the F-Test (Anova) no Fulfill beliefs ANOVA (additive, normality, homoscedasticity, independence) though already conducted transformation, then an alternative final our can test it using the Kruskal-Wallis Test ( One Way Anova - RAL ) or Friedman Test (RAK) which is a technique statistics non-parametric.

Based on the amount variable:

  • Statistics Univariate: technique analysis statistics that only involve one dependent variable.
  • Statistics Multivariate: technique analysis statistics involving more than one dependent variable at once.

Role statistics in the study:

  • Give information about characteristics distribution something population-specific, fine discrete, or continuous. Knowledge, this helpful in live behavior moderate population is observed.
  • Provide procedure practical in conducting surveys to collect data through method data collection (sampling technique). Knowledge of this practice for getting results reliable measurement.
  • Provide procedure practical for guessing characteristics, something population through approach characteristics samples well through method assessment, method testing hypothesis, method analysis variance. Knowledge this useful for knowing size centering and size deployment as well as differences and similarities in populations.
  • Provide procedure practical for fortune telling state something object certain in the future based on past and present circumstances. Through method regression and method row time. Knowledge of this useful zoom-out risk consequence uncertainty faced in the future.
  • Provide a procedure practical for to do testing data that is qualitative through non-parametric statistics.

Connection Statistics with Method Study

Statistics is one component main in stages method research, determining size sample, collecting, presenting, and analyzing data as well as for seeing degrees scientific.

After the article titled Definition Statistics by General and Definition Complete will Citra invite you to read the article statistics next. So don't forget to stop at Blog Statistics to get knowledge and benefits from statistics world learning by deep and complete. When you still there are questions, please leave comments.

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