Data and statistics
Discover how to find, evaluate and interpret data and statistics.
Go to: What are data and statistics? | Finding | Evaluating | Resources
What are data and statistics?
The terms data and statistics are often used interchangeably. However:
- Data are the facts, evidence, observations, or experiences obtained through research. Data collected is analysed, then used to underpin the answer to a specific research question, or to validate findings. Data is often numerical, but may be descriptive, oral or visual, and can be in print, digital or physical format.
- Statistics refers to the analysis, interpretation, and presentation of data. Statistics can help you to understand and analyse situations and events. They are often presented in tables, charts, or graphs, but you will also see them reported as numbers or percentages in articles.
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Finding published data and statistics
You’ll find data and statistics in research articles and papers following a literature search, and in a range of statistical resources, including:
- Eurostat: The statistical office of the EU, providing high quality statistical data on Europe.
- Office for National Statistics: Collects and publishes statistics related to the economy, population, and society across the UK, at national, regional, and local levels.
- Passport: Market research tool which monitors and analyses industry trends in countries around the world. Login with your university username and password.
- UK Data Service: Provides access to a collection of social, economic, and population data, for teaching, learning, and the public.
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Evaluating, interpreting and analysing data and statistics
It’s important that you critically evaluate any statistical data you find before using it in your work.
Statistics can be valuable evidence, but they can also misrepresent or distort situations or events, either intentionally, or unintentionally. This could be a result of:
- Selective use of data or misleading language
- Different interpretations of statistical data
- Flawed data collection and analysis
To help you decide if a source of statistical information would be useful for your work, consider the following questions:
Who?
Authority and intended audience
- Who compiled the data / statistics? Was it a commercial organisation? Was it a government body? Might this have introduced bias?
- Who will make use of, or benefit from, these data / statistics? Is there an intended audience? Might this have introduced bias?
Where?
Type of publication and data source
- Where have the data / statistics been published?
- Is it a primary or secondary source? If a secondary source, has it been referenced correctly so you can find the primary source?
- Is it a publication intended for a specific audience? Might the choice of publication have introduced bias?
- When were the data / statistics published?
- What is the date range of the data / statistics? Is it historical or current?
- Is the date of publication / date range relevant to your work?
Why?
Production , purpose and use
- Why have the data / statistics been produced?
- What was their purpose? How have they been used?
- Has any bias been introduced to emphasise a particular outcome?
How?
Data collection and analysis
Data collection
- How was the data collected? What variables or categories were identified? What units of measurements were used?
- How was the population / sample group identified prior to data collection? Was it a random selection, or was a specific group targeted? Might this have introduced bias?
- What was the size of the population / sample group? Was it large enough to present data as percentages?
Data analysis
- How was the data analysed? What tests were used?
- How do the data / statistics relate to the text? Do the data / statistics support what is being said about them?
- What decisions (or even assumptions) may underpin the questions asked, the statistical processes used, and the analysis provided?
Presentation?
Visual communication and meaning
- What is being shown in the data / statistics?
- How are the data / statistics being presented?
- Could the way the data / statistics are presented have introduced bias, or be conveying hidden messages?
For example:
- Has colour been used to emphasise certain aspects of the data? Why have these areas been selected in particular? Might this be conveying an implicit message of relative importance?
- How have graphs, tables, pie-charts and other visual forms of data presentation been used to display the data? Have some areas been given greater emphasis? Why might these areas have been selected? Has this introduced bias?
- How are axes on any graphs labelled? Are they clear and appropriate?
Critical evaluation resources
The following resources provide further guidance to help you critically evaluate statistical data:
- Full fact: An independent fact-checking organisation based in the UK, which reviews evidence for, and corrects, claims reported in the news and on social media.
- How to spot spin and inappropriate use of statistics (PDF): House of Commons research briefing which provides tips and guidance to help you identify ways in which statistics can be used inappropriately.
- Introduction to data and analytics: This resource provides access to a range of free, high quality, online courses to help you develop your skills and knowledge in data analytics and data science. Log in to this resource on Moodle using your university username and password.
Data analysis resources
You may also find the following resources helpful for data analysis.
To access them, log in to our Data management resource (within Digital Student on Moodle) using your university username and password:
- Statistics Launchpad: To help you develop your understanding of different statistical concepts and equations, and how they are used in the real world.
- Statistical Analysis Support System (SASS): To help you make informed choices on which statistical software package to use to analyse data collected for your own research.
Digital Student - Moodle
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