# Data Analysis Services

Data analysis is the scientific process of establishing an objective meaning(s) from unprocessed/partially-processed information. Statistical data analysis is a major section of data analytics that is centred on making meaning of data that can be expressed in numerical terms. In other words, data-analysis is a value-addition process that makes otherwise useless data elucidative, descriptive, predictive or interpretive.

Statistics data analysis is mainly guided by the nature of the data and the objectives of the data analysis efforts.

The nature of the data:

• Is it qualitative or is it quantitative?
• Is it static or dynamic?
• Is it primary data or secondary data?
• Is it structured or is it unstructured?
• Is it hybrid?

Objectives of statistical data analysis:

• Descriptive: To describe relationships, objects, occurrences or phenomenon.
• Exploratory: To understand unknown or partially-known elements in relationships, objects, occurrences or phenomenon.
• Causal: The find out how a change in a variable(s) will affect the relationships, objects, occurrences or phenomenon related to that variable
• Predictive: To predict the end result of defined interactions amongst relationships, objects, occurrences or phenomenon
• Inferential: To apply discoveries in relationships, objects, occurrences or phenomenon to a wider population

The nature of the data together with the objectives of the data analysis exercise will assist in the identification of the most appropriate data analysis methodology.

Statistical data analysis services

We offer professional data analysis services to academics, businesses and professional entities. Our data analysis services include:

1. Data structuring
2. Data capturing
3. Data analysis and interpretation
4. Findings Reporting
5. Findings Presentation
6. Research Designing
7. Research Report editing
8. Secondary data analysis (Review of literature)

Statistical data analysis steps

At MathsGee, our statistical data analysis processes are listed below. To fully capture your data analysis and presentation expectations we:

1. Understand your data analysis goals and objectives
2. Study your data, the data capturing and collection processes
3. Determine the appropriate tests based on your objectives and on the nature of your data
4. Data cleaning: Clarify and correct data inconsistencies
5. Capture/Export data to SPSS
6. Conduct relevant data reliability and validity analyses
7. Carry out the appropriate or required tests
8. Present the data (textual, graphical and tabular formats)
9. Prepare a complete data analysis report as per your format
10. Forward the completed report to you for review
11. Fine tune any matters as per your suggestion