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Module

PSY1014 : Research Methods and Data Analysis B

  • Offered for Year: 2024/25
  • Module Leader(s): Dr Hannah Roome
  • Owning School: Psychology
  • Teaching Location: Newcastle City Campus
Semesters

Your programme is made up of credits, the total differs on programme to programme.

Semester 2 Credit Value: 20
ECTS Credits: 10.0
European Credit Transfer System

Aims

The aim of this module is to further expand student’s knowledge of open and transparent research. The focus of this module is to build upon research methods and data analysis training in semester 1 (PSY1013 or PSY1012) and for students to gain further practical experience as a researcher. Students will carry out experimental quantitative designs and practice how to produce rigorous and reproducible projects. Students will continue to develop their data processing skills. To continue their teaching of data analysis techniques, students will develop knowledge of appropriate statistical testing in quantitative designs.

They will practice communication of their findings in the form of a scientific report. This will further facilitate student’s ability to appraise scientific claims in psychology, and develop their skills as an independent researcher.

Outline Of Syllabus

For students to learn independent research skills, they will gain first-hand experience in quantitative data collection. Students will further consolidate their understanding of different quantitative research designs by developing knowledge of the use of appropriate statistical methods using a statistical toolbox. This will include being taught about central tendency, variability, data distribution, and the principles of hypothesis testing, as well as how to compute and interpret parametric and non-parametric statistical tests.

Students will communicate their findings in the form of lab report which adheres to a common standard for scientific report writing, e.g. the American Psychological Association (APA) format. Students will have awareness of different research paradigms and approaches.

Teaching Methods

Teaching Activities
Category Activity Number Length Student Hours Comment
Guided Independent StudyAssessment preparation and completion701:0070:00Assessment preparation for the summative assignments, problem-based exercises and written statistical exam
Scheduled Learning And Teaching ActivitiesLecture111:0011:00PiP lectures
Structured Guided LearningAcademic skills activities111:0011:00Non-synchronous online components as pre-learning for the data analysis and research methods workshops (formative practice activities, quizzes)
Scheduled Learning And Teaching ActivitiesWorkshops112:0022:00PiP Data analysis practical sessions
Scheduled Learning And Teaching ActivitiesWorkshops111:0011:00PiP Research methods skills
Guided Independent StudyStudent-led group activity14:004:00Quantitative experimental data collection
Guided Independent StudyIndependent study701:0070:00Independent study
Scheduled Learning And Teaching ActivitiesModule talk11:001:00Non-synchronous online recorded lecture to introduce the module
Total200:00
Teaching Rationale And Relationship

The overall aim of this module is to equip students with the practical skills to be an independent researcher. Therefore, the structure of this module is to provide a theme each week, outlined in the opening lecture. This will provide students with the necessary knowledge and information required to conduct each component of the scientific process that is being practised that week. This will be further enhanced by additional independent reading and the completion of practice activities prior to their practical workshops.
For the practical sessions, students will continue to work in their small groups from PSY1013, with a demonstrator to practically carry out the tasks for the week. This is broken down into two practical workshops 1) research methods and 2) data analysis. The research methods component will finalise the practical components of how to carry out quantitative methods, data collection, and how to disseminate research effectively via a laboratory report. The data analysis practical workshops will teach students how to organise and manage the data collected, consolidate their ability to create effective visualisations, and carry out inferential statistics.

Assessment Methods

The format of resits will be determined by the Board of Examiners

Exams
Description Length Semester When Set Percentage Comment
Written Examination902A50This will be a PiP statistics exam whereby students can use their notes and logbook created during the module. Textbooks are not allowed.
Other Assessment
Description Semester When Set Percentage Comment
Practical/lab report2M50Quantitative Lab Report 1 x 1500 word practical report reporting inferential statistics.
Formative Assessments

Formative Assessment is an assessment which develops your skills in being assessed, allows for you to receive feedback, and prepares you for being assessed. However, it does not count to your final mark.

Description Semester When Set Comment
Report2MMock Pre-Registration Report A 750-word report for the quantitative research project, the rationale for why the study was carried out, and the research design, and statistical test chosen.
Assessment Rationale And Relationship

The assessments provide students with the opportunity to develop and practice the necessary skills that map onto the skill outcomes of this module. Students will be required to submit one laboratory report following the quantitative strand of this module which will follow the standard APA guidelines for report writing. This will include a Title, Introduction, Methods, Results, Discussion, References and any necessary Appendices. The ability to analyse, present and interpret experimental data, as well as their scientific written communication will be assessed by the written report. The word limit for each report is 1,500 words following APA guidelines.
A formative assignment will provide students the opportunity to practice building a concise rationale for a quantitative research project. This will provide feedback on their ability to write concisely and will feed into the Introduction of their quantitative report. This will also include describing the research design and appropriate statistical tests required, which will provide input for both the methods and results components of their report.
The statistics exam is designed to assess the current state of the students’ statistical knowledge. This will be achieved using 4 questions with multiple elements.
In order to pass this module, students are required to attain a pass mark in both of the assessment components.

If the module is failed students will resit failed assessments in the same format during the August resit period.

Reading Lists

Timetable