Data analysis is the process of examining data to find answers to questions. There are many ways that you can analyse and display data. This module will give an overview of some common analysis methods and tools. The data can be read through and manually organised by you, or processed using software.
- Get an overview of your data
- Descriptive data analysis
- Inferential data analysis
- Data visualisation
- Misrepresenting data
- Tools for analysing and visualising data
- Look through, or listen to, all the data you have gathered to get an overall idea of what you have gathered
- Transcribe any audio content so it is ready to be organised. You can record directly in Word for web or upload an audio file to get a transcription.
- Think about how you can reveal patterns or meaning in the data
- You may be able to sort the qualitative data in a way that it can be measured.
Read the blog – How we helped our reporters learn to love spreadsheets.
You can access the Times data training program in Google Drive, including training information, datasets and tip sheets to learn skills for Google Sheets and using data to tell a story.
Descriptive analysis provides a summary of the data that has been gathered. For quantitative data this involves presenting the data visually in tables and charts, and measuring values such as the mean. For qualitative data the data is interpreted through grouping into categories or coding. Coding is the process of organising and sorting your data.
You can use one method or a mix of methods to do your analysis. Methods include:
- Classification — sorting the data into different kinds of things
- Statistical analysis — for qualitative data this could be counting different elements, such as keywords and phrases, to find out how often something is mentioned or has occured.
- Thematic analysis — looking for recurring themes in the data.
Thematic analysis of qualitative data
Looking for patterns or themes in your data can help to answer your original question or may lead to new questions. Descriptive coding is a useful technique for thematic analysis. Coding can be done by hand or by using software, such as NVivo.
Descriptive coding by hand
Statistical analysis of quantitative data
Statistical analysis methods can range from simple to complex. Simple methods include:
- Range — the difference between the highest and lowest value
- Minimum — the smallest value
- Maximum — the largest value
- Frequency — the number of times a certain value appears
- Mean — the total of the values divided by the number of values
- Median — the middle value of any data after they are put in order
- Mode — the most frequently occurring value.
You can use data analysis software to perform the statistical analysis.
How to use features in Microsoft Excel to analyse data, including sort, filter, charts and pivot tables. It includes step-by-step tutorials on the different functions.
Inferential analysis involves using the information from the data to make judgements about a topic or issue. For example, the results from a small group could be used to infer something about a larger group, or the results could be used to predict what might happen. Inferential analysis of qualitative data usually requires more advanced statistical methods
Which Stats Test (UQ login required) is a question tool to help you narrow down the type of statistical test to use.
Tables, graphs, maps and charts are used to summarise and display data. Once you have done your analysis you need to think about the best way to present the data.
Examples of data visualisations
The Tudor Networks visualisation brings together 123,850 letters connecting 20,424 people from the United Kingdom’s State Papers archive, dating from the accession of Henry VIII to the death of Elizabeth I (1509-1603).
Charting culture (YouTube, 5m 36s) is a visualisation of cultural mobility tracking the births and deaths of notable individuals like David, King of Israel, and Leonardo da Vinci, from 600 BC to 2014:
The following visualisation shows the average years of schooling per country from 1950 to 2017:
Choosing a chart
- Chart Chooser is a tool to help you find the right chart to display your data. After you choose the type of chart, you can download an Excel or PowerPoint template and then insert your own data.
- Chartopedia has a guide for choosing the right chart type.
- Picking the right chart for your data (LinkedIn Learning, 1h19m) Main topics include getting to the key idea you’re trying to communicate; finding the right standard chart for your data type; and brainstorming and experimenting to come up with alternatives to the standards.
- Our Data visualisation guide has information on techniques, tips and tools to display data.
- The Communication Learning In Practice for Scientists (CLIPS) website has guidance on communicating results with scientific graphs.
- The Data visualisation catalogue shows different information visualisation types.
- Look at the Periodic table of visualisation methods for ways to display your data.
Graphs can make data easier to understand but they can also be used to misrepresent data. Check graphs carefully. The graph creator can manipulate the design to inaccurately reinforce their own agenda.
- omitting baselines to make one group look better than another
- manipulating the y-axis to blow out the scale
- only including certain parts of the data
- choosing a type of chart that does not fit the data
- using colours, that alter long-held conventions or associations.
There are many tools available for analysing and visualising data. You may want to use a tool that you have some experience with already, like Excel or Google Sheets, or you may want to try using software that is specifically for data analysis.
These tools can be used to analyse and visualise data
|Tool||Useful features and limitations||UQ Library training||Online training guides and courses|
|Microsoft Excel||Microsoft Excel is the standard spreadsheet tool commonly used in workplaces. It is recommended if you need a full range of specialized functions for data analysis and organisation tasks.||Yes||Excel Essential Training (Office 365) (LinkedIn Learning, 2h24m)|
|Google Sheets||Google Sheets is a free, web-based tool for creating spreadsheets and requires a Google Account to use. To access Sheets offline you need to use the Google Chrome browser and install Google Docs offline Chrome extension.||No||Google Sheets Essential Training (LinkedIn Learning, 1h52m)|
|Calc (LibreOffice)||Calc is a free spreadsheet tool you can download to your computer. Calc does allow you to share spreadsheets so multiple users can add data, however, real-time collaboration is not supported. File formats are compatible with Excel.||No||Learn LibreOffice Calc 6 in Under 30 Minutes (YouTube, 22m3s)|
Data and text analysis software
These tools can be used to analyse and visualise data.
|Tool||Useful features or limitations||UQ Library training||Online training guides and courses|
|Matlab||Matlab is downloadable software you can use for data analysis, modelling and visualisation. UQ students can download MATLAB to their personal computers.||No||Learning MATLAB (LinkedIn Learning, 1h13m)
Course: MATLAB 2018 Essential Training (LinkedIn Learning, 3h15m)
|Python||Python is a programming language that can be used for data analysis and visualisation.||Yes||LinkedIn Learning pathway - Python|
|R and RStudio||R is a language and environment for statistical computing and graphics. RStudio is an integrated development environment (IDE) to make R easier to use.||Yes||Pathway: LinkedIn Learning pathway - R.
Resources - used in our different R courses.
|SAS||SAS's Education Analytical Suite is a data analytics tool available to be downloaded by UQ students.||No||Getting Started with SAS Studio|
|SPSS||SPSS Statistics is a software package used for statistical analysis and is available for UQ students to via Zenworks on Library Computers and in HASS/HABS Student Computer Labs.||No||Video: Introduction to SPSS for data analysis (YouTube, 16m17s).
Course: SPSS Statistics Essential Training (LinkedIn Learning, 5h49m)
|KNIME Analytics Platform||Use KNIME Analytics Platform to create data workflows, perform different analysis steps and display the results as models or interactive views for interpretation. KNIME analytics platform is available as a free open source desktop application under the GNU General Public Licence.||No||Resources from KNIME to get you started.
Data Science Foundations (LinkedIn Learning, 4h3m) - sections on KNIME.
Geographic information systems (GIS) tools
GIS tools are used to capture, analyse and present spatial or geographical data
|Tool||Useful features and limitations||UQ Library training||Online training guides and courses|
|Carto||Carto is a cloud-based GIS platform built on open source software. Students can use Carto for free via the GitHub Student Developer Pack.||No||Carto tutorialsCarto tutorials|
|ESRI ArcGIS||ESRI ArcGIS is a downloadable tool for building and analysing geographical information. Students may use ArcGIS within specific courses. View the UQ Map Gallery from ArcGIS .||No||ArcGIS Pro Essential Training (LinkedIn Learning, 3h17m).|
|Google Earth||Google Earth is a free mapping tool available online, via your desktop, or on your mobile device.||No||Become a Google mapping expert|
|QGIS||QGIS is a free, open-source desktop application for creating, editing and analysing geospatial information.||Yes||Course: Learning QGIS (LinkedIn Learning, 2h57m)
Guide: QGIS Training manual
Our Geographic information systems (GIS) guide lists other tools and software to use with spatial or geographical data.
You can find more tools for analysing, visualising and presenting data in our Choose the right tool module.