2018/19 Undergraduate Module Catalogue

LLLC0144 Data Handling

10 creditsClass Size: 30

Module manager: Lynne Cade
Email: e.a.cade@leeds.ac.uk

Taught: Semester 1 (Sep to Jan) View Timetable

Year running 2018/19

This module is not approved as a discovery module

Objectives

To equip students with knowledge of a range of essential descriptive statistics, and a range of techniques and computing skills required for data handling and undergraduate study

Learning outcomes
Knowledge of :
-the scientific nature of measurement
-validity and reliability of measurement
-measurement conversion
- different measures of central tendency and variability;
- descriptive statistics;
- the basic functions of SPSS;
- basic experimental design and issues involved in working with human participants.

Skills outcomes
Ability to :
- Choose perform and interpret appropriate statistical tests;
- apply an understanding of statistical outputs and reports;
-convert measurements between scales;
- use Word and SPSS to produce professional data Tables and Figures, and report results
- use SPSS to enter data and conduct basis statistical procedures.

Syllabus

Types of research methods, Types of data, the scientific method, Understanding and calculating measures of central tendency and variance. Entering data into SPSS, Using SPSS to calculate descriptive statistics, understanding of the normal distribution, validity and reliability, number conversion, groups, Using Word for presenting data in research reports.

Teaching methods

Delivery type	Number	Length hours	Student hours
Workshop	3	5.00	15.00
Seminar	12	3.00	36.00
Independent online learning hours			25.00
Private study hours			24.00
Total Contact hours			51.00
Total hours (100hr per 10 credits)			100.00

Private study

Time for private study is expected to break down as follows:
Independent on-line learning 25 hours
Preparation for seminars 12 hours
Preparation for assessments 12 hours

Opportunities for Formative Feedback

Formative assessments will feature throughout the module to prepare students for and familiarise students with the main assessments. These will include submission of short calculations expected of the students in later assessments. It will also include submission of short exercises examining knowledge of descriptive statistics, experimentation, science, Word and SPSS. These formative assessments will be crucial to gauge the progress of students, to ensure the concepts and techniques are understood and to build confidence. This is particularly important for this module as statistics is typically an area which students find difficult. All of the types of questions featured in the final assessments will be tackled at some stage in the formative assessments.

Methods of assessment

Coursework

Assessment type	Notes	% of formal assessment
Written Work	4 Written assignments, Will be graded pass/fail	0.00
In-course Assessment	1 hour MCQ	40.00
Report	Statistical Analysis 1,500 Word Equivalent	60.00
Total percentage (Assessment Coursework)		100.00

Normally resits will be assessed by the same methodology as the first attempt, unless otherwise stated

Reading list

The reading list is available from the Library website

Last updated: 12/12/2018 16:33:09

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