Statistical Data (Importance, Analysis, Methods, Types and Purposes)

 Statistical Data Analysis 

Statistical data analysis is the science of collecting data, information and unpairing patterns to use that data and analyze it according to a specific method.

 The Importance of Statistical Data Analysis 

Without a doubt the statistical data analysis is very important in the completion of the research paper since it is considered as a part of the methodology procedures. 

1. Statistical data analysis summarizes the data in small sentences which help the researchers easily understand it.
2. Statistical data analysis makes future predictions based on past behavior that is useful in banks and manufacturing.
3. Statistical data analysis used for Test an experiment’s hypothesis and how successful they are.
4. Statistical data analysis helps researchers to find key measures of location easily for example the mean.

This article contains topics in which the researchers provide such information that clarifies statistical analysis, data analysis methods, data analytics and statistical data. 

 Statistical Analysis 

Statistical analysis is the use of statistical data including various variables, entities, and events to know probabilistic and statistical relationships and analyze it to quantitative manner that can simply read and understand and get the key measures and use it in theses, dissertations or projects.

 Statistical Analysis and the Scientific Method 

1. Questions: every survey or process of data collection need a base of specific questions, the answers to these questions are the information and data needed to make statistical analysis.
2. Background Research: researchers should do background research to find if there were any statistical analysis or data collection made upon the same topic in the past to avoid mistakes.
3. Make hypothesis: hypothesis is a theory that is fair in order to explain certain events or phenomenon for now. This hypothesis generally uses questions based on real life consisting variables and quantities which we can measure in order to create specific statistical statements about them. That hypothesis should be tested.
4. Analyze results and draw conclusions: this stem is necessary to know if our hypothesis is true or false if it is false, we must start again and find a new hypothesis to make sure the statistical analysis is good enough and persuasive.
5. Writing and reporting results: in this method of the statistical analysis, researcher should write the benefit of this statistical analysis.

 Data Analytics 

Data analytics is the science of analyzing raw data in order to make conclusions about that information.

Data analytics is a spacious and comprehensive term for many different types of data analysis. It is a very important step where any type of information can be subjected to data analysis techniques to get an idea that can be used to improve the outputs of data analysis.

 Types of Data Analytic 

• Descriptive analytic: it describes changes has changed over a given period of time. This process provides important look into past performance.
• Diagnostic analytic: it focuses on why changes happened in a specific period. 
• Predictive analytic: it predicts what is likely going to happen in the near term Based on what was deduced from the data and data analysis based on historical data to identify trends
• Prescriptive analytic: it suggests a course of action (how does the best way get done?)

 How to become a Data Analyst? 

Data analysts translate information into data.  A Data Analyst delivers value by taking information about specific topics and then interpreting, analyzing, and presenting feedback in overall reports.

 What is the purpose of data analysis in scientific research? 

Data analysis in scientific research aims to achieve several things, the most important of these things:

1. To clarify the relationship between the impact and the cause of one of the phenomena that the researchers are studying, so that researchers are able to conceptualize things and events.
2. Researchers get answers to the questions they have in mind about the phenomenon they are studying.
3. To reach conclusions that relate to a phenomenon.
4. To search for a phenomenon, and then link this phenomenon to reality and study the dimensions and implications, and search for the ideal ways to deal with them.

 Watch: Statistical questions | Data and statistics 

With greetings: Al - Manara Consulting to help researchers and graduate students