2020/21 Undergraduate Module Catalogue
LLLC0144 Data Handling
10 creditsClass Size: 25
Module manager: Lynne Cade
Email: e.a.cade@leeds.ac.uk
Taught: Semester 1 (Sep to Jan) View Timetable
Year running 2020/21
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 studyLearning 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 websiteLast updated: 30/06/2020 18:16:17
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- Undergraduate module catalogue
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