Analysis helps to find meaning behind the data, and extract the answers to important questions. Analysis can be done once the data has been scraped and cleaned using a variety of formulae which are often particular to the software being used (Microsoft Excel, Google Spreadsheets, SPSS etc.)
Here are some useful questions to ask yourself when you are about to analyse some data:
- What am I trying to find out?
- Are there any trends in the data?
- Is the data telling a story?
- What seems to be the norm? Are there any anomalies?
- Does the data reveal something other than the hypothesis?
- School of Data: Analysing data - This course walks you through the basics of analysis, including using formulas and manipulating the data to create new values: http://schoolofdata.org/handbook/courses/analyzing-data/. There are many pitfalls to avoid when analysing data, many of which are outlined here: http://schoolofdata.org/handbook/courses/common-misconceptions/
- Data Analysis in Microsoft Excel - This guide has broken down the different ways to analyse data in Microsoft Excel: http://www.excel-easy.com/data-analysis.html
- Data Analysis in SPSS - This is a comprehensive guide to analysing data in SPSS, walking through each tool for analysis and how to use it effectively: https://students.shu.ac.uk/lits/it/documents/pdf/analysing_data_using_spss.pdf
- Data Analysis in Google Spreadsheets - Here is the list of Google Spreadsheet functions: https://support.google.com/docs/table/25273?hl=en&page=table.cs&rd=1