1. Introduction to the use of data and analysis
Dr Sofia Izquierdo-Sanchez
Senior Lecturer in Economics
Co-Deputy Director Research Centre for Productivity Improvement (RCPI)

2. Be open to unanticipated patterns and results
You may have a story to tell and data can help you to solve the problem.
You don’t always have to start with a question, data may come first (“Data Mining”)
Have an open mind and be prepared to explain unexpected results

3. Explain things and measure their value
We use data to describe an issue or to solve a problem.
The results we obtain have to be transformed and organised to be presented to the relevant audience.
Data can be in different forms:
Qualitative
Quantitative

4. Text: words and/or descriptions
Qualitative data: Data can come from interviews, open-ended questions on a survey, etc. For example: gender, race, or the description of an object.
Although it may seem difficult to use this data for our purposes, most of the times it contains valuable information we cannot ignore in our analysis.
Think that this data can be easily transformed to quantitative data to satisfy our purposes.

5. Numbers
Quantitative data: Usually data is expressed with numbers. For example: age, rating scales, or length.
Quantitative data can be divided in groups (“categorical data”), and so one id (item, person, etc) cannot belong to more than one group at a specific time.
Quantitative data can be measured on a continuous range of scale (“continuous data”)

6. Is your data telling a story?
The aim is to make statements about a population. However we cannot have information about a whole population. We need to select a sample from the population of interest.
Is this sample representative?
Problems:
Bias
Outliers
Missing data
etc.

7. Different types of data, different types of research
Qualitative research: it explains how, within a particular context, an occurrence operates.
Quantitative research: it explores the (causal) relationship between two events or occurrences, where one of the events is a consequence of the other one.

8. Qualitative vs Quantitative
Qualitative Research
Quantitative Research
Type of knowledge
Subjective
Objective
Aim
Exploratory and observational
Generalisable and testing
Characteristics
Flexible
Fixed and controlled
Contextual portrayal
Independent and dependent variables
Dynamic, continuous view of change
Pre- and post- measurement of change
Sampling
Purposeful
Random
Data collection
Semi-structured or unstructured
Structured
Nature of data
Narratives, quotations, descriptions
Numbers, statistics
Value uniqueness, particularity
Replication
Analysis
Thematic
Statistical
Note: (1) definitions and table can be found at: “6 methods of data collection analysis”. Monitoring, Evaluation, Accountability and Learning (MEAL), Open University.

9. Wide range of statistical packages

10. A question for you
Are you interesting in learning more about data analysis or about any of the statistical packages? Let us know 

11. Northern Productivity Hub
For information about the Northern Productivity Hub and their goals and services visit their webpage: