Thursday, 17 December 2020

Statistical communication theory


Statistical communication theory. Statistical analysis is a type of analysis that is undertaken and performed when planning a project, or when conducting scientific research.


Statistical communication theory

Conducting a successful statistical analysis is one of the most important reasons for the success of the project or scientific research presented by the researcher, given the valuable information provided by the statistical analysis.


Types of statistical analysis


statistical analysis:

It is the scientific method through which the researcher prepares scientific data, in order to conduct analysis on it, and extract information useful for scientific research through it, so that this information is new and of valuable benefit.


statistical analysis:

It is the scientific process through which the researcher talks about society, explains the characteristics of this society, and identifies the features that distinguish this society from other societies.


In order for the researcher to reach the information that distinguishes society from the rest of societies, he must take a sample from the community, in order to conduct a study on it according to logical foundations, and extract from it the characteristics that can be generalized to society, and thus determine its distinctive characteristics.


What are the steps of statistical analysis?

1- There is a set of steps that a researcher must take in order to conduct a distinct statistical analysis of his scientific research.


2- In the beginning, the researcher must choose the type of statistical test, and this choice is made according to a number of principles, and the most prominent of these principles are:


A- The type of private data that is directly related to the dependent variables.

B- The type of relationships that the researcher wishes to test and conduct statistical analysis thereof.

C- Determining the number of independent variables that the researcher will study.

D- And then determine the number of levels of independent variables.


3- After the researcher chooses the type of statistical test, he must possess the sufficient ability to distinguish between parameter tests and non-parameter tests, and we will explain this difference as follows:


A - The parameter tests have certain features, and the most prominent of these features is the fulfillment of the hypothesis that states that the type of data for which the researcher conducts statistical analysis is at the level of the period scale.


The distribution of the study population must be normal. In addition, the research population must contain the same differences that exist in the research sample that will be subjected to statistical analysis.


B- As for the non-parametric tests, they have a set of features, such as fulfilling the hypothesis that the type of data should be at the level of a hierarchical scale only. In addition, the study population must be freely distributed.


4- After the researcher has seen that the researcher is acquainted with the parameter tests and the non-parameter tests, he must choose the appropriate type of test, and the teacher tests have a set of advantages over non-parameter tests, and the most prominent of these features are:


A- The teacher tests are more powerful in case they are compared to the non-parameter tests.

B - Parametric tests have a great ability to identify all indications that concern important differences.

C- Parametric tests use all the information contained in the collected data.

D- The non-parametric tests sola are not concerned with arranging the data only.

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