How To Do The Statistical Analysis Of The Data
During your professional career you may need to support your work with the ‘ statistical analysis of data. A study, a revolutionary approach to the marketing strategy you are following, the specific request of a client: in short, you may come across the numbers and you will need to be able to face them in the best possible way, so that they support your theses with favor. But, first of all: what is statistical data analysis? As often happens, a good definition from Wikipedia helps us: ” Data analysis is a process of inspecting, cleaning, transforming and modeling data with the aim of highlighting information that suggests conclusions and supports strategic business decisions. “Here it is, exactly what you might be called upon to do, or help do for a client or a client.
How is the statistical analysis of the data done?
Data analysis finds application in the social sciences, natural sciences, business and business dynamics, and intelligence. In short, it embraces many fields including marketing.according to Animation Video Service There are several techniques and models that we will not investigate because they are the subject of real university subjects. What we are interested in telling you is how to do a statistical analysis of the data and, above all, why it is done. Starting from this last statement, the data analysis is done to prove something. Through the data (which will be provided to you or which you yourself will have collected previously), you can:
Define what to do
Define why to do it
Interpret what has been done
To perform (in the method) a statistical analysis of the data correctly, you must start from a main question and then extrapolate a series of increasingly specific sub-questions which you will then answer through the data you have collected or that have been provided to you. You will have to answer each question by associating a numerical quantity.
There are two types of data that you can find yourself in front of. Here’s what to do in each case:
Qualitative variables (profession of the sample, gender, educational qualification)
Quantitative variables (income, age, etc.)
In the first case you have to extrapolate a numerical data , collecting in the table how many people in the sample are male / female, how many have a degree or a lower educational qualification, etc. In the second case, however, having already to do with numerical data, you will have to extrapolate:
The standard deviation (also called standard deviation)
The (possible) interquartile range, or the dispersion difference. It is used to measure how far the data deviates from a central value.
Subsequently, you will have to report everything in graphs and tables that are as simple and complete as possible, in order to allow speakers and clients to read quickly and easily.
Software for statistical data analysis
Often the analysis of statistical data is used for predictive purposes (i.e. to predict a specific behavior or result and consequently make business choices). Many other times, especially when you want to prove or support a thesis, the data are used for descriptive purposes. In both cases, statistical algorithms and machine learning techniques are used.
In almost all cases, especially for the management and manipulation of large amounts of data and variables, both paid and free software for data analysis are used. Among the free alternatives that you may find yourself using (even as a simple support to the company department that uses it) there are:
Knime Analytics to model data through visual programming
Open Refine to manage and manipulate unorganized data (through cleaning, organization and formatting of unorganized data to make them more modelable)
Tableau Public able to extract data not only from Excel files but also from Google files, CSV files, etc. and able to allow the publication of interactive data on the web.
You can also do statistical analysis with Excel, the spreadsheet included in the Microsoft Office package. Online there are several tutorials that teach how to set up a statistical analysis – even a rather complex one – with this tool. Those mentioned and many others (even paid or premium versions) are software used for business data analysis.
Of course, you don’t necessarily have to know and master statistical data analysis techniques and programs. If your field is another and has little to do with statistics and mathematics, but you have been told anyway to bring an analysis to support your strategic choices, you can request the collaboration of a professional who carries out statistical analysis by profession. Incorrect statistical conduct leads to incorrect choices, so it is better to start immediately on the right foot and avoid losing time and money due to incompetence.