## 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:
Module version for: 2016/7

Module Convenor: Dr Kou Murayama

Summary module description:
The module will provide a basic understanding of strategies of data analysis and their applications to psychological research. It will ensure that students can apply and interpret core descriptive and inferential statistics, and will enable them to use suitable computer packages (e.g. MicroSoft Excel, Open Office Calc, SPSS, GPower) for these purposes.

Aims:
The module will provide a basic understanding of strategies of data analysis and their applications to psychological research. It will ensure that students can apply and interpret core descriptive and inferential statistics, and will enable them to use suitable computer packages (e.g. MicroSoft Excel, Open Office Calc, SPSS, GPower) for these purposes.

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 parametric and nonparametric statistical methods.
• describe, interpret and comment on results of SPSS analyses that use these methods.

The student will gain practical experience of using the packages Excel, SPSS and GPower to manage and present data, and to implement statistical methods covered in the module. These will not be assessed directly in this module, but may be in the co-requisite module PYM0S2. The 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 parametric and nonparametric methods for descriptive statistics and exploratory data analysis. Significance, effect size and statistical power. Core parametric and nonparametric methods for univariate and bivariate inferential statistics, including 1-sample and 2-sample tests on means, correlation and regression. Use of SPSS and GPower for these analyses and for data manipulation and management.

Brief description of teaching and learning methods:
1.Preliminary diagnostic exercise on core statistical methods. Students whose prior knowledge of these is shown by the diagnostic exercise to be limited, will receive additional backup teaching. 2.Directed reading of books and articles. This preparatory work will be done in advance of associated seminars. 3.Seminars (drawing on the preparatory work) to discuss principles of statistical techniques, their assumptions, purpose and limitations. 4.Self-paced statistical computing practical classes with demonstrator support.

Contact hours:
 Autumn Spring Summer Seminars 10 Practicals classes and workshops 10 Guided independent study 80 Total hours by term 100.00 Total hours for module 100.00

Summative Assessment Methods:
 Method Percentage Class test administered by School 100

Other information on summative assessment:
Assessment will be by an open-book test in the week following the completion of the taught part of the course. The test will include (a) short-answer questions on statistical concepts and (b) on the choice of statistical methods suitable for specific purposes (c) questions which present the outputs of SPSS data analyses, from described psychological studies, and require the student to report and interpret the results of the analysis, with comments.

Formative assessment methods:
Students are given feedback on a preliminary statistics assessment, and there is the opportunity to develop skills during practical sessions.

Penalties for late submission:
Penalties for late submission on this module are in accordance with the University policy. Please refer to page 5 of the Postgraduate Guide to Assessment for further information: http://www.reading.ac.uk/internal/exams/student/exa-guidePG.aspx

Length of examination:

Requirements for a pass:
50%

Reassessment arrangements:
A failed test may be taken again in the Spring term, by arrangement with the Course Director.