FURTHER STATISTICS AND DATA ANALYSIS - 2017/8
Module code: PSY1021
ASKEW C Dr (Psychology)
Number of Credits
FHEQ Level 4
Module cap (Maximum number of students)
Overall student workload
Workshop Hours: 22
Independent Study Hours: 108
Lecture Hours: 22
|Assessment type||Unit of assessment||Weighting|
|Coursework||QUANTITATIVE ASSIGNMENT (4 PAGES)||25%|
|Coursework||QUALITATIVE ASSIGNMENT (4 PAGES)||25%|
|Examination||MULTIPLE CHOICE EXAM (1 HOUR)||50%|
Prerequisites / Co-requisites
Prior completion of PSY1020 Introduction to Statistics and Data Analysis is required
This module will follow on from the semester 1 module entitled ‘Introduction to Statistics and Data Analysis I’. It will involve a combination of lectures and workshops. The module will both further students’ understanding of quantitative methods and introduce qualitative research methods. With regard to the qualitative component of this module students will be introduced to: 1. the key principles and characteristics that distinguish qualitative research and; 2. methods of generating data commonly used by qualitative researchers (next year they will be introduced to methods of qualitative data analysis). Each lecture will cover a particular research issue/theory, a quantitative analytic procedure or a method of qualitative data generation, the basis of which will be explored using illustrative research and other examples and in-class experiments/group work. The workshops will focus on ‘practising’ the largely theoretical content of the preceding lecture, using quantitative data sets to be explored and analysed and qualitative data generation exercises from a student-led approach. These will provide opportunities to reflect on and apply theoretical knowledge and contexts for reflecting critically upon these experiences to yield a firm grounding in quantitative methods and methods of generating qualitative data in psychology.
This module aims to develop students' understanding of and ability in quantitative data analysis and qualitative data generation – core skills required in psychology research and practice. Data analysis in psychology draws upon on a multitude of differing methods, which can be broadly subsumed into two groups: quantitative and qualitative methods. This module will cover quantitative data analysis and qualitative data generation to ensure that students: (a) clearly understand the different characteristics and principles associated with quantitative and qualitative research; (b) are provided with a basis for engaging with the research literature that utilises these methods; (c) are themselves capable of independently analysing quantitative data and reporting their findings; (d) are able to formulate a qualitative research question; (e) can develop, use, and reflect on using a semi-structured interview schedule; and (f) are equipped to engage in an informed way with the coverage of qualitative data analysis in the Year 2 module entitled ‘Applied Critical Thinking and Qualitative Data Analysis’, where they will be introduced to various methods of qualitative data analysis. Taken together the material relating to qualitative methods learned from this module and Applied critical thinking will equip students’ with the necessary skills and understanding to undertake a qualitative research project for their dissertation should they so wish
|Have a more developed understanding of the assumptions underpinning and procedures involved in test selection and power analysis||KC|
|Understand a broader range of statistical analyses and be able to perform them correctly, interpret their output appropriately and report this in the correct format.||KCP|
|Understand the underlying assumptions of ANOVA, be able to interpret interactions, trends and contrasts||K|
|Be aware of the purpose of follow-up analyses and the ways in which they can be calculated and interpreted||K|
|Understand the key characteristics and principles associated with quantitative and qualitative research||KCPT|
|Appreciate the utility of qualitative methodology and analysis||KCPT|
|Understand how to formulate qualitative research questions||KC|
|Be able to develop a semi-structured interview||KCP|
|Have experience of interviewing using a semi-structured interview schedule||KPT|
|Understand the interpersonal skills required to conduct a good quality interview||KCPT|
|Be able to critically reflect on their experience of developing and implementing an interview schedule||KCPT|
|Understand and be able to identify the appropriateness of using various methods of qualitative data generation in different research contexts||KCPT|
C - Cognitive/analytical
K - Subject knowledge
T - Transferable skills
P - Professional/Practical skills
The weekly lectures and workshops will cover theory and practice including and related to the following indicative topic areas:
Analysis of Variance (ANOVA), including factorial ANOVA
Follow-up tests and assumptions
Further nonparametric tests
Qualitative research methods, including key principles, interviewing, reflection and qualitative data analysis
Methods of Teaching / Learning
The learning and teaching strategy is designed to:
foster independence in statistical skill
enable students to understand research findings originally reported
promote a critically evaluative approach to quantitative and qualitative methods
equip students with an understanding of the key principles and characteristics of qualitative methods
give students knowledge of a range of data generation techniques used by qualitative researchers
give students experience of formulating a qualitative research question
give students the opportunity to develop a semi-structured interview schedule and conduct an actual interview
foster the ability to critically reflect on the research process (both in terms of devising an interview schedule and in conducting an interview).
The assessment strategy is designed to provide students with the opportunity to demonstrate
The first assessment is a quantitative assignment worth 25%, designed to encourage test selection skill, independence in running a range of different statistical analyses (from both this module and those covered in PSY1020). The assignment will consist of datasets requiring students to utilise a considered and statistically evaluative approach, and to make inferences about data normality, test assumptions, to select most appropriate follow-up tests and report these in a concise and correctly formatted manner. The learning outcomes in relation to quantitative methods will be assessed in this assignment including subject knowledge, analytical and transferable skills, the latter in relation to format and presentation of results specific to the psychology discipline.
The second (qualitative) assignment is also worth 25% and will consist of an interview schedule (developed by working with a small group of students), and a reflective essay in which the student will reflect both on their experience of conducting an interview and on the utility/effectiveness of their interview schedule. This assignment will assess the students’ ability to formulate a qualitative research question, as well as their understanding of, and ability to develop a semi-structured interview (the main method of data generation used by qualitative researchers). It will also assess their ability to critically reflect on the research process, which is a key skill required of qualitative researchers. All of these are key learning outcomes of the qualitative component of the module.
The third assessment (a 60 minute, 40 question MCQ exam worth 50%) is designed to test all learning outcomes relating to the quantitative components of the course, with emphasis on subject knowledge. The exam is designed to assess the full breadth and depth of the quantitative module content, with questions specific to each class and essential readings.
Formative assessment and feedback
Weekly quantitative methods workshops typically consist of questions and data sets to analyse. Students will receive feedback in the form of a written feedback sheet to enable them to check their progress. They also receive individual verbal guidance and feedback from a class tutor on request. In the final weeks before the exam, and throughout the quantitative part of the module, students will complete MCQ questions and receive feedback to enable them to check their understanding of the module content and become familiar with the MCQ format.
The qualitative workshops are structured around the second assignment and focus on giving formative feedback in relation to this particular assessment. Student group discussions in which they formulate their research question and develop their interview schedules will be facilitated by the tutors, giving students feedback directly relating to their assignment. General class feedback will be given to the students based on the tutor’s observations of the interviews conducted in class. This will help students reflect on their own experience of being an interviewer. Students will also be asked to discuss in groups the utility/effectiveness of their interview schedule; what they learned from using it and how they might change it based on this experience. These discussions will be facilitated by the tutors, which in turn will feed-forward in to the students’ critical reflection on this for their assignment.
Reading list for FURTHER STATISTICS AND DATA ANALYSIS : http://aspire.surrey.ac.uk/modules/psy1021
Please note that the information detailed within this record is accurate at the time of publishing and may be subject to change. This record contains information for the most up to date version of the programme / module for the 2017/8 academic year.