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Introduction to the use of data and analysis

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). Be open to unanticipated patterns and results. You may have a story to tell and data can help you to solve the problem.

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Introduction to the use of data and analysis

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  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 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: https://www.hud.ac.uk/business/northernproductivityhub/ E-mail: productivity@hud.ac.uk

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