PY0761 - Psychological Data Analysis

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What will I learn on this module?

This module provides you with an introduction to quantitative and qualitative data analysis. The main focus is on the analysis of quantitative data, which arise from measurement. Quantitative analysis, also known as statistics, makes up about 85% of the module. In this part you will gain a good understanding of fundamental concepts and principles in statistics. These include levels of measurement; standardised effect size measures; sample distributions, standard errors and confidence intervals; and statistical significance testing and the problems it causes. This basic understanding will allow you to independently read advanced literature on statistics to further your own understanding. In addition to basic principles, you will also learn about a range of frequently used techniques for data analysis. For each of them you will learn to identify when it is suitable to use; how to run the analysis; how to report its results to experts and lay people; and how to use these result to inform your critical judgement about your own research and that of others. The techniques you will learn about include the estimation of standardised effect sizes; meta-analysis; ANOVA and ANCOVA; multiple regression; and chi2 to analyse proportions. Finally, you will learn about the limitations of statistical inference in some important real-world settings.
In the qualitative data analysis part (about 15% of the module) you will learn a number of techniques and the theories behind them to analyse verbal data, as they arise from interviews, panel discussions and similar.

How will I learn on this module?

During teaching weeks, you will have a weekly two-hour session that comprises interactive lecture, seminar, and workshop components. Here you will acquire basic knowledge about syllabus topics, critically apply this new knowledge in group work and discussions, and gain hands-on experience in data analysis. You will be provided with regular exercises to do on your own time to further develop your understanding and skills. Independent reading on the module topics is highly recommended. Online discussion groups encourage all students to form an interactive learning community. Individual tutorials will be available to discuss your learning or to help you if you get stuck.

How will I be supported academically on this module?

You have two hours of scheduled teaching during teaching weeks. Tutors are also available for you via email, the online discussion forum, or for individually arranged tutorials. All lecture and workshop materials are available online in the PY0728 site on Blackboard, including annotated lectures slides and video recordings of the lecture parts. These online materials help you to catch up on sessions you might miss and to revisit content to deepen your understanding of the subject matter. Regular exercises with worked answers and other materials for guided learning will be available. You will also be provided with advice for your independent learning.

What will I be expected to read on this module?

All modules at Northumbria include a range of reading materials that students are expected to engage with. The reading list for this module can be found at: http://readinglists.northumbria.ac.uk
(Reading List service online guide for academic staff this containing contact details for the Reading List team – http://library.northumbria.ac.uk/readinglists)

What will I be expected to achieve?

Knowledge & Understanding:
? MKU1: By the end of the module you will understand fundamental concepts and principles in statistics.
Intellectual / Professional skills & abilities:
? MIPSA1: By the end of the module you will be able to independently read advanced literature on statistics to further your own understanding.
? MIPSA2: By the end of the module you will be able to appropriately apply the techniques for data analysis outlined in the syllabus, report their results in an adequate way, and use these results to critically evaluate your own research and that of others

How will I be assessed?

You will be regularly provided with exercises to do on your own. As these come with worked solutions, you can use these exercises for formative assessment.
The first assessment is an assignment at the end of Semester 1. This contributes 33% towards your module mark. The assignment addresses fundamental concepts and principles in statistics. (MKU1,MIPSA1)
With your mark, you will receive detailed written feedback about the strengths and ways to improve your paper.
The second assessment is a seen open-book exam at the end of Semester 2. This contributes 67% towards your module mark. The exam assesses module learning outcome 3. You will be given a number of data sets to analyse and draw appropriate conclusions. Incomplete data sets will be provided for the seen version of the exam. You will receive this seen version some weeks before the actual exam and can therefore plan the analyses you want to run and how to report them. The complete data sets will only be available during the exam. You can use all your notes during the exam. (MKU1, MIPSA2)
With your mark, you will receive detailed written feedback about the strengths and ways to improve your solutions.

Pre-requisite(s)

N/A

Co-requisite(s)

N/A

Module abstract

Psychology is an empirical science, i.e. it uses actual data to shape and test ideas about behaviour and the mind. Relevant data typically derive from measurements and are then in the form of numbers; sometimes our data are verbal instead, e.g. when we interview someone. In either case, it is not trivial to make a connection between our data and the ideas that inspired our research. In this module you will learn how to do that. These skills are crucial in order to develop your own research and to fully understand and evaluate the research of others. As this module is mostly about statistics, many students approach it with trepidation. However, students enjoy this module (typically against their expectations) because they get to know exciting ideas and insights, and the hands-on training provides them with a range of data-analysis skills that are important in research and beyond.

What will I learn on this module?

This module provides you with an introduction to quantitative and qualitative data analysis. The main focus is on the analysis of quantitative data, which arise from measurement. Quantitative analysis, also known as statistics, makes up about 85% of the module. In this part you will gain a good understanding of fundamental concepts and principles in statistics. These include levels of measurement; standardised effect size measures; sample distributions, standard errors and confidence intervals; and statistical significance testing and the problems it causes. This basic understanding will allow you to independently read advanced literature on statistics to further your own understanding. In addition to basic principles, you will also learn about a range of frequently used techniques for data analysis. For each of them you will learn to identify when it is suitable to use; how to run the analysis; how to report its results to experts and lay people; and how to use these result to inform your critical judgement about your own research and that of others. The techniques you will learn about include the estimation of standardised effect sizes; meta-analysis; ANOVA and ANCOVA; multiple regression; and chi2 to analyse proportions. Finally, you will learn about the limitations of statistical inference in some important real-world settings.
In the qualitative data analysis part (about 15% of the module) you will learn a number of techniques and the theories behind them to analyse verbal data, as they arise from interviews, panel discussions and similar.

Course info

Credits 20

Level of Study Postgraduate

Mode of Study 2 years part-time
1 other options available

Department Psychology

Location City Campus, Northumbria University

City Newcastle

Start September 2019

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