Analysis and Interpretation

Data analysis and data interpretation are closely related, but have different meanings. Lets first define the meaning of the word data. Data is defined as factual information that can be used as a basis for reasoning, discussion, or calculation. There are several different types of data. It can also be defined as information output by a sensing device or organ that includes both useful and irrelevant or redundant information and must be processed to be meaningful. Now that data has been defined, in order to put together the meaning and uses of data analysis and interpretation, analysis and interpretation would need meaning and definition as well.
Analysis is a word that is used to define separation or breakdown of something whole into its separate components. In reference to data, data analysis is a breakdown of information and facts that were compiled or processed to form data. Data analysis includes inspection of data, cleaning, transforming, and modeling data to form supportive information. Data analysis is a process that contains several phases. There are two parts that are clearly defined, that is initial and main data analysis. Data cleaning is a relevant procedure that is is used to ensure the high quality of data and the opportunity to make corrections to any incorrect or improper data. During this process data is documented, corrected, and saved.
An example of data analysis would be individuals’ submitted answers to a survey or poll. Their submissions would be processed to form data. So all of their submissions would be the data analysis. The results of the poll or survey would lead to interpretation.
Interpretation involves action. Data interpretation is applying statistical procedure to analyze specific facts from a study of body of research. It is the act or result of interpreting. It can be described as an explanation of results or reasoning. Interpretation is used to define data or justify actions due to received data. It is often