Overview
Subject to validation
Discover the stories hidden in the numbers and build the skills you need to make smart, evidence-based decisions. Get hands-on experience with real datasets, master data visualization, and use industry-standard tools like Excel, and open-source software packages like R and SQLite to turn complex info into insights that matter.
Start dates:
October 15: Online live session
Weeks 1 and 2: Asynchronous online learning (learn in your own time)
October 22: Chase Stadium (in person)
Weeks 3 and 4: Asynchronous online learning (learn in your own time)
November 12: Chase Stadium (in person)
Teaching Modality
Duration
Price
Award
Key benefits
Develop practical data analysis skills
Gain hands-on experience working with large datasets using industry-standard tools such as Excel, R, and SQLite to uncover meaningful insights.
Master data visualization techniques
Create compelling charts, graphs, tables, and visual reports that communicate complex information clearly and help stakeholders make informed decisions.
Earn a professional credential from UEL
Enhance your analytical expertise while earning a professional certificate from one of the United Kingdom's leading career-focused universities.
Who should enroll?
Organizations rely on data to drive strategy, measure performance, and solve complex problems. Our Professional & Executive Education program is designed for professionals who want to strengthen their analytical capabilities and make more informed, evidence-based decisions.
- Individuals looking to build confidence using Excel, R, SQLite, and other data analysis tools
- Professionals interested in developing practical experience with statistical analysis and data visualization
- Managers and leaders seeking to use data to guide strategy and organizational performance
Have questions?
Got a question? Get in touch with us.
FAQs
What is the difference between quantitative and qualitative data analysis?
Quantitative analysis examines numerical data to measure patterns, differences or relationships. Qualitative analysis examines language, experience and meaning using sources such as interviews, observations or documents. Quantitative research methods can answer questions using numerical data, while qualitative methods can explain context and why people experience an issue in a particular way.
What is the difference between descriptive and inferential statistics?
Descriptive statistics summarize the data available, for example through averages, ranges or distributions. Inferential statistics use a sample to estimate or test claims about a wider population while accounting for uncertainty. A quantitative data analysis program should help learners distinguish a useful summary from a conclusion that requires statistical inference.
Do I need advanced mathematics to learn quantitative data analysis?
Introductory data analysis usually requires comfort with numbers, proportions and logical reasoning rather than advanced mathematics. The level of mathematics required increases with techniques such as regression or probability modelling. More important at the start is understanding the question, the type of data and what a result can and cannot demonstrate.
Where are quantitative analysis skills used professionally?
Quantitative analysis training is relevant to business, public health, marketing, finance, operations, policy, research and program evaluation. Professionals use numerical evidence to compare performance, identify trends, evaluate outcomes and support decisions. The same calculation may have different meaning depending on the quality of the data and the context in which it was collected.
How can analysts avoid drawing misleading conclusions from data?
Analysts should check data quality, sample size, missing information, bias and whether the method matches the question. They should avoid treating correlation as proof of causation or presenting precise numbers without explaining their limitations. A quantitative data analysis program can strengthen the judgement needed to interpret and communicate results responsibly.