PYM0S1-Data Collection & Analysis 1

Module Provider: Psychology
Number of credits: 10 [5 ECTS credits]
Level:7
Terms in which taught: Autumn term module
Pre-requisites:
Non-modular pre-requisites:
Co-requisites: PYM0S2 Data Collection and Analysis 2
Modules excluded:
Current from: 2022/3

Module Convenor: Dr Anthony Haffey
Email: anthony.haffey@reading.ac.uk

Type of module:

Summary module description:

Via seminars and workshops theÌýmodule will enable students to apply and interpret core descriptive and inferential statistics using R, thus developing anÌýunderstanding of strategies of data analysis and their applications to psychological research.

Aims:

The aim of theÌýmodule is to enable students to developÌýa basic understanding of strategies of data analysis and their applications to psychological research using R.

Assessable learning outcomes:

By the end of the module, students should be able to: show knowledge of the purpose, conceptual basis, assumptions and limitations of core statistical methods and describe, interpret and comment on results of R analyses that use these methods.

Additional outcomes:

The student will gain practical experience of using the package R to manage and present data, and to implement statistical methods covered in the module.ÌýThe content of this module will be drawn upon in many parts of the programme, including module PYM0S2 (the next level of statistical training), in practical assignments (e.g., PYM0EP) and in theoretical or evaluative aspects of other modules.

Outline content:

Principles and practice of core statistical analysis, including descriptive statistics, data transformation, correlation, regression, t-test, hypothesis testing, effect size, confidence intervals and statistical power.Ìý

Brief description of teaching and learning methods:

1. Lectures on statistical principles and analysis, with some self-directed activities (not counted for the final mark) to consolidate learning. 2. Directed reading of books and articles on statistical issues not covered by the lectures. 3. Self-paced statistical computing practical classes with demonstrator support.

Contact hours:

Ìý	Autumn	Spring	Summer
Seminars	10
Practicals classes and workshops	10
Guided independent study:	80
Ìý	Ìý	Ìý	Ìý
Total hours by term	100
Ìý	Ìý	Ìý	Ìý
Total hours for module	100

Summative Assessment Methods:

Method	Percentage
Written assignment including essay	100

Summative assessment- Examinations:

Summative assessment- Coursework and in-class tests:

Students complete an assignment in which they will be expected to analyse data in R and report on the outcomes using techniques learned during the module.

Formative assessment methods:

Students will receive ongoing feedback during the practical sessions, and are invited to discuss their assignment outcome in a one-to-one meeting.

Penalties for late submission:

The below information applies to students on taught programmes except those on Postgraduate Flexible programmes. Penalties for late submission, and the associated procedures, which apply to Postgraduate Flexible programmes are specified in the policy £Penalties for late submission for Postgraduate Flexible programmes£, which can be found here: /cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmissionpgflexible.pdf
The Support Centres will apply the following penalties for work submitted late:

• where the piece of work is submitted after the original deadline (or any formally agreed extension to the deadline): 10% of the total marks available for that piece of work will be deducted from the mark for each working day (or part thereof) following the deadline up to a total of five working days;
• where the piece of work is submitted more than five working days after the original deadline (or any formally agreed extension to the deadline): a mark of zero will be recorded.

The University policy statement on penalties for late submission can be found at: /cqsd/-/media/project/functions/cqsd/documents/cqsd-old-site-documents/penaltiesforlatesubmission.pdf
You are strongly advised to ensure that coursework is submitted by the relevant deadline. You should note that it is advisable to submit work in an unfinished state rather than to fail to submit any work.

Assessment requirements for a pass:
50%

Reassessment arrangements:

If a student fails the assignment, an alternative, equivalent assignment can be submitted.Ìý The assignment and date of submission will be by arrangement with the Module Convenor and/or Programme Director. Students should note however that, given the University regulations on failing credits, it may not be in their interests to resubmit the coursework.

Additional Costs (specified where applicable):

1) Required text books:Ìý

2) Specialist equipment or materials:Ìý

3) Specialist clothing, footwear or headgear:Ìý

4) Printing and binding:Ìý

5) Computers and devices with a particular specification:Ìý

6) Travel, accommodation and subsistence:Ìý

Last updated: 21 November 2022